A phosphorescence method to probe protein dynamics

A P H O S P H O R E S C E N C E M E T H O D T O P R O B E P R O T E I ND Y N A M I C S

gusztáv schay

supervisor : prof . judit fidy d.sc .

Doctoral School of BiologyDoctoral school leader: Prof. Anna Erdei D.Sc.

Structural Biochemistry doctoral programme , Eötvös Lóránd UniversityProgramme leader: Prof. László Gráf D.Sc.

Department of Biophysics and Radiation BiologySemmelweis University

June 2012

Gusztáv Schay: A phosphorescence method to probe protein dynamics, © June

2012

A B S T R A C T

A new phosphorescence-based method is presented, by which the acti-

vation of slow (ms - s time-scale) global dynamics of proteins can be

monitored. It is shown, that the activation of this slow, global dynamics

is specific for the protein. A simple model is also presented by which

the activation energy and entropy can be calculated (estimated) from the

experimental data. The new method is presented in the case of human

hemoglobin. The experiments were performed also in the presence of al-

losteric effector molecules, which modify the oxygen-binding of hemoglobin.

As a consequence of the presence of these effectors we have observed

changes in the activation of the collective dynamics of hemoglobin, changes

in the dissociation constant of the tetramer obtained by pressure pertur-

bation, and also changes in the isothermal compressibility obtained by

fluorescence line narrowing spectroscopy. All these changes are in accor-

dance with the efficiency of the effectors in modifying the oxygen bind-

ing of hemoglobin. This shows that changes in the global, slow dynamics

of hemoglobin, caused by allosteric effectors may play a significant role

in the regulation of hemoglobin function. The phosphorescence-based

method is also applied to two other proteins, namely phosphoglycerate

kinase, and dUTP-pyrophosphatase. In the case of phosphoglycerate ki-

nase it was shown that the activation of the dynamics is asymmetric, and

depends on the presence of both domains. Apparently, the hinge-bending

motion is not essential for the inter-domain communication: there is a col-

lective dynamics of the two domains even when hinge bending is blocked.

In the case of dUTP-pyrophosphatase it was shown that the C-terminal

arm-like structures of the trimeric molecule have a distinct dynamics in

the apo-enzyme and in the substrate-bound form. It may thus be hypoth-

esized that the special type of dynamics being monitored in these exper-

iments may be important in the regulation of multi-domain proteins.

iii

C O N T E N T S

General introduction 1

i dynamical transition in hemoglobin 9

1 the dynamical transition 11

1.1 Introduction 11

1.2 Methods 12

1.2.1 Sample preparation 12

1.2.2 Phosphorescence decay measurements at various tem-

peratures. 14

1.2.3 Evaluation of phosphorescence decay curves 15

1.2.4 Adjusting the temperature of the sample 18

1.2.5 Further control experiments 21

1.3 Results of the dynamical transition 24

1.3.1 Phosphorescence lifetime of Zn-PP in HbA as a func-

tion of temperature 24

1.3.2 Mechanisms underlying the two steps of phospho-

rescence quenching of Zn-HbA 27

1.4 A simple model 35

1.4.1 Qualitative model of the thermal activation of mil-

lisecond protein dynamics. 37

1.4.2 Quantitative model of the first transition 39

1.4.3 Analysis of the thermodynamic parameters 41

2 biological significance 45

2.1 Allosteric effectors 45

2.2 Effectors and the transition 48

2.2.1 Activation of global dynamics in the presence of al-

losteric effectors. 48

2.2.2 Analysis of the differences caused by allosteric ef-

fectors 52

3 changes at the interfaces - pressure perturbation 57

3.1 Introduction to pressure perturbation studies 57

3.2 Method of pressure perturbation 58

3.2.1 Fluorescence Emission Spectra under High Pressure 58

3.2.2 Absorption Spectra at High Pressure 60

3.2.3 FTIR Spectroscopy Under Pressure 60

3.3 Pressure perturbation results 61

v

3.3.1 Control experiments 61

3.3.2 Transitions seen in the Trp fluorescence 65

3.3.3 Transition seen in HbA is not caused by denatura-

tion 65

3.4 Discussion of the pressure perturbation results 69

3.4.1 The transition is related to dissociation. 69

3.4.2 A simple model of the pressure-induced dissocia-

tion 73

3.4.3 Analysis of the data 76

4 relation to compressibility 79

4.1 Introduction to Fluorescence Line Narrowing 79

4.2 Compressibility results 84

4.3 Discussion of compressibility 90

5 summary 93

ii application to other proteins 97

6 phosphoglycerate kinase 101

6.1 Introduction to PGK 101

6.2 Transitions in PGK 103

6.3 Inter-domain interactions in the dynamical transition 105

7 dutp-ase 109

7.1 Short introduction to dUTP-ase 109

7.2 Transition in dUTP-ase 111

8 closing remarks 115

bibliography 121

iii appendix 135

a phosphorescence setup III

a.1 System design III

a.2 Controller program VI

a.3 Micro-controller HUB XI

a.4 Web-server architecture XVI

b fln setup XIX

b.1 Laser scanning XIX

b.2 Data evaluation XX

vi

L I S T O F F I G U R E S

Figure 1 Reference absorption spectrum of Zn-HbA. 13

Figure 2 Sample decay curves of Zn-HbA at various temperatures. Thefitted curve is shown in red, the result of the MEM is shownon the right together with the lifetime and relative weight ofthe discrete exponentials. 17

Figure 3 a: Comparison of the average lifetime (<t>) values for Zn-HbA measured using the two different protocols: “fast cool-ing” (red) and extreme rapid cooling (grey). A cooling path(returning from 230 K) is shown in black. The error bars indi-cate the estimated absolute error of the <t> values.b: Comparison of the <t> values of fast cooling protocol (redcurve, and red axis) and deliberately slow cooling protocol(brown curve and axis). The error bars indicate the estimatedabsolute error of the <t> values. 20

Figure 4 Absorption spectra of Zn-HbA. Freshly thawn Zn-HbA is shownin black (identical to Figure 1) and after an experiment involv-ing the fast cooling technique (green curve) together with thedifference spectrum at 50x magnification (grey dotted line).Spectrum taken after the deliberately slow cooling techniqueis shown in red. Curves are shifted along the absorbance axisfor clarity. 23

Figure 5 Normalized average phosphorescence lifetime values of Zn-HbA (red curve) and Pd-CP (blue curve). The negative deriva-tive functions are also shown. The lines are fitted functionsto the original data shown with symbols. (Our own modelfunction to the first transition and a sigmoid curve to the sec-ond) 28

Figure 6 Normalized average lifetime data of Zn-PP in DMSO (greenline and symbols). For comparison Zn-HbA data is also shown(red curve). 29

Figure 7 Normalized average lifetime data of partly deoxygenated Zn-HbA (orange curve, triangles). For comparison the curves ofnormal Zn-HbA (red) and Pd-CP (blue) are also shown. 30

Figure 8 Normalized average lifetime of Zn-HbA in 60% v/v glycerolmixture (black symbols and curves). For comparison Zn-HbAunder the usual conditions is also shown with red. 32

Figure 9 Normalized average lifetime of the Trp residues in Zn-HbA(blue curve and symbols). The error is also shown, since it islarger than 5%. For comparison the data of Zn-PP in Zn-HbAis also shown (red curves). 33

Figure 10 Normalized average lifetime of Myoglobin (dark green lineand symbols). For comparison the Trp data of Zn-HbA is alsoshown. For clarity only the error bars of Mb data are shownon the graph. 34

vii

Figure 11 Arrhenius plot of the Zn-HbA data (red) and Zn-PP/DMSOdata (green) overlay-ed with Fig.4 from [35]. BA,DA and “exit”represent various rate constants measured in Mb, while a andb represent the two types of fluctuations. 36

Figure 12 Qualitative model of the dynamic transition. Zn-HbA data areshown in red, the pictograms represent three different statesas discussed in 1.4.1. 38

Figure 13 Atomistic crystal structure of hemoglobin (T-state, bound toinositol hexaphosphate). The individual subunits are each col-ored differently for clarity, the Zn-PP substitution of the hemegroups in the b-subunits is marked with green, two of the sixTrp-s are marked with red, the inter-dimeric interface region isemphasized with a brown line. 46

Figure 14 Schematic representation of the rotation of the two dimers withrespect to each other during the transition between the twostates of R and T. 49

Figure 15 Oxygen binding curve of hemoglobin. The curve shows theoxygen saturation curve of the whole tetrameric molecule, thus100% saturation is equivalent to the total binding of 4 oxygenmolecules. The shifting of the curve to the right (decreasedbinding affinity) is caused by allosteric effectors, and is shownwith an arrow. In the bottom of the figure the structure of threedifferent allosteric effectors are also shown. 50

Figure 16 Normalized average lifetime of Zn-HbA bound to Cl-(purplecurve and diamonds). For comparison stripped Zn-HbA is alsoshown with red. The negative derivative functions are alsoshown in the bottom graph. 51

Figure 17 Normalized average lifetime of Zn-HbA bound to IHP (bluecurve and triangles). For comparison stripped Zn-HbA is alsoshown with red. The negative derivative functions are alsoshown in the bottom graph. 52

Figure 18 Normalized average lifetime of Zn-HbA bound to DPG (or-ange curve and triangles). For comparison stripped Zn-HbAis also shown with red. The negative derivative functions arealso shown in the bottom graph. 53

Figure 19 Normalized average lifetime of Zn-HbA bound to BZF (darkgrey curve and triangles). For comparison stripped Zn-HbA isalso shown with red. The negative derivative functions are alsoshown in the bottom graph. 54

Figure 20 Comparison of the first transition of Zn-HbA under variousconditions: stripped (red), with added Cl-(purple), with addedDPG (orange) and added BZF (dark grey). The respective deriva-tive functions are also shown in the bottom. To emphasize theimportance of the first transition, the second half of the curvesare shown in pale colors. 55

viii

Figure 21 The current high pressure setup. Drawing of the high-pressurecell, image of the modified spectrometer, and of the wholesetup. Light paths are shown in blue / light green for exci-tation / emission respectively, the used quartz cuvette is alsoshown with its stopper. 59

Figure 22 FTIR spectra of HbA and Mb at ambient pressure (blue lines),at 325 MPa (red line) and at 900 MPa (black line). The posi-tion of the position of the amide-I peak of a-helical content atvarious pressures are also shown for HbA (squares) and Mb(triangles) together with their s.d. 62

Figure 23 Absorption spectra of HbA at ambient pressure (blue line)and at 350 MPa (red line). Inset shows the absorption max-imum of the Soret-band around 409 nm at various pressurelevels. 63

Figure 24 Fluorescence emission spectra of Zn-HbA at ambient pressure(blue line) and at 350 MPa (red line). Inset in the figure showsthe peak position of the Q-band of Zn-PP at various pressurelevels. Excitation was at 290 nm wavelength. 64

Figure 25 Excitation spectrum of Zn-PP in Zn-HbA. 65

Figure 26 Trp fluorescence emission of oxy-HbA at ambient pressure(blue line) and 3.5 kbar (red line). The inset shows the nor-malized emission spectra to emphasis the spectral shift accom-panying the intensity increase. 66

Figure 27 Fluorescence emission of Zn-HbA at various pressure levels.The top figure shows the maximum position of the emission,the bottom figure shows the emission intensity at the maxi-mum. Insets in both figures show the respective data for Mb. 67

Figure 28 Concentration - dependence of the p½data in oxy-Hb (squares)and Zn-HbA (diamonds). 72

Figure 29 Summary of the changes in equilibria caused by allosteric ef-fectors 77

Figure 30 Demonstration of the FLN technique. Upper figure shows theordering of molecules on the energy-scale, bottom figure showsthe fluorescence emission by a narrow-band excitation. See textfor details. Figure reprinted with permission from [68] 80

Figure 31 Comparison of room-temperature emission spectrum (blue line)and FLN resolved emission spectrum (red line) of Zn-HbA. 81

Figure 32 Schematic representation of the FLN experimental setup. Thebottom left picture shows the photograph of the diamond cellmounted on the cold-finger of the cryostat, the small mirror isused to direct the excitation light (green line) to the sample,while the big mirror is placed into the setup for photographicpurposes, only to show the other side of the cell. The upperright picture shows the setup with the cryostat closed and op-erating. 85

Figure 33 A sample series of resolved spectra. The sample is Zn-HbA +100 mM NaCl at 1.4 kbar. The spectra are shifted along theintensity axis for clarity. The excitation laser scanned the rangeof 17840 cm-1 ... 18214 cm-1. 86

ix

Figure 34 The IDF of Zn-HbA + 100mM NaCl at 1.4 kbar. The figureshows the raw output of the IdfFit program as an illustrationof the calculation of the IDF. The program also reports the pa-rameters of a Gaussian fitting to the data. 87

Figure 35 Shifting of the IDF due to increasing hydrostatic pressure. Asan example the IDF-s of Zn-HbA + 100 mM NaCl is shown,and for clarity the individual data-points are omitted, and theIDF-s are shifted along the vertical axis. The pressure levels inkbar units, corresponding to each curve, are shown in the topof the figure. The shift of the IDF-s is not proportional to thepressure increase. 88

Figure 36 IDF position and width values (with s.d.) for various Zn-HbAsamples under pressure. 89

Figure 37 Overlay of the IDF shifts of Zn-HbA in the stripped (red, squares),with 100mM NaCl (green, triangles) and 10mM BZF (orange,triangles). 91

Figure 38 Schematic representation of the PGK structure, showing thehinge region as well. The domain abbreviations are shown indark red color (N, C, N*C and C*N). The sequence differencesbetween the engineered constructs is presented in the table be-low the structures. Figure reprinted from [94] with permission.102

Figure 39 Sample decays of the PGK N domain construct at various tem-peratures. The line represents the fit to the data as in Figure 2.Two kinds of distributions are shown: obtained by MEM (pan-els to the right) and by allowing only a sum of gaussian distri-butions in the decay-rate space (middle panels). 104

Figure 40 Average lifetime values of the four different PGK constructs atvarious temperatures. The solid lines are the fits to the dynam-ical transition. The error bars show the s.d. of the data. 105

Figure 41 Schematic representation of DUT, the three subunits are col-ored differently. The key residues of the active sites are shownin a ball-and-stick model, note the long chain of the “arm”originating from the third subunits, and reaching the activesite. Figure is reprinted from [147]. 110

Figure 42 Decay curves of Trp phosphorescence in apo- human DUTat various temperatures: 10 K (blue) 210 K (red) and 235 K(green) 111

Figure 43 Temperature dependence of the average lifetime of human DUTin the apo form (blue squares) and bound to dUPNPP (greentriangles). For comparison, the fitted curves of Pd-CP (darkgreen line) and stripped Zn-HbA (red line) scaled up to fit thegraph are also shown. 112

Figure 44 Picture of the integrated phosphorescence lifetime spectrome-ter. The main blocks are marked in the picture. IV

Figure 45 Block diagram of the new system design. VFigure 46 Image of the CCU main board (top, © G.Schay) and block di-

agram of the propeller chip (bottom, image used with permis-sion from the Parallex website) XII

x

Figure 47 The first page of the web-site of the data-acquisition programas displayed on a remote computer. XVIII

Figure 48 Image of the laser-scanning program, together with a list offiles of the source code. XIX

Figure 49 Output of the “Peakfinder” program of the FLN data evalu-ation package. The sample is Zn-HbA + 100 mM NaCl at 1.4kbar pressure. XXI

L I S T O F TA B L E S

Table 1 Parameters of the selected discrete exponential fittings. The re-marks show the classification of the lifetimes as well. The life-times below 0.2 ms are arising from the 80ms sampling time-quantization, and were discarded from further analysis, there-fore these are not shown in the table, but are shown in Fig-ure 2. 16

Table 2 <t> data of the chromophores at 10K temperature. 27

Table 3 Thermodynamic parameters of fitting to the first transitionstep: DE (energy change), DS (entropy change), TMP (midpointtemperature), and Kd ( = t0/ td ) , ± s.d. 42

Table 4 Average phosphorescence lifetime of Zn-HbA bound to allostericeffectors. For comparison the data of stripped Zn-HbA is alsoshown in this table. 49

Table 5 Thermodynamic parameters of the first transition in differentZn-HbA samples. For comparison the data from Table 3 of thestripped from (and calculated from Zn-PP lifetimes) are alsoshown ± s.d. 53

Table 6 Mid-transition pressure values (p½) of oxy-HbA and Zn-HbAunder different conditions. 70

Table 7 Kd0 and DV data of oxy-HbA and Zn-HbA under various con-ditions, and at 60mM concentration. The relative error of thedata is approximately 5%. 75

Table 8 Parameters of linear regression of the shift of the IDF data.Note, that the slope of the IDF-center (dn0/dp) is proportionalto the isothermal compressibility (k). 91

Table 9 Parameters of the dynamical activation of PGK constructs. 106

xi

N O M E N C L AT U R E

BZF Bezafibrate

DMSO dimethyl sulfoxide

DPG 2,3-diphospho-glycerate

dUPNPP 2´-deoxyuridine-5´-(a,b-imido)triphosphate

DUT dUTP-ase

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

IDF inhomogeneous distribution function

IHP Inositol hexaphosphate

Mb Human Myoglobin

MEM Maximum Entropy Method

MWC Monod-Wyman-Changeux model of allostery in hemoglobin

oxy-HbA oxygen - saturated, R-state HbA

Pd-CP Palladium coproporphyrin

PGK Phosphoglycerate kinase

TRP Tryptophan residue

Zn-HbA [a-FeO2]2-[b-Zn]2-HbA

Zn-PP zinc protoporphyrin-IX

FLN Fluorescence Line Narrowing Spectroscopy

HbA Human Hemoglobin A

xii

From where then does wisdom come,and where is the resting-place of knowledge?

For it is kept secret from the eyes of all living,unseen by the birds of the air...

...for we see now through a mirror obscurely,and then face to face.

— Bible 1

G E N E R A L I N T R O D U C T I O N

There is so much to say about the selected citation from the Bible. Beyond

its deep theological message - which shall not be discussed in this the-

sis - it can be understood in a broader context covering all wisdom and

knowledge, including the purpose of our lives. At the same time, it also

holds in a much more limited context: the knowledge of science.

Since science and philosophy have seemingly departed from each other,

it might appear a little confusing to start a PhD dissertation in the field

of science with a discussion about general wisdom. However, ultimately

science is all about “wisdom” in a special way: we would like to acquire

knowledge about nature, about the world around us, and - as a result of

a motivation working deeply inside us - about the purpose of our lives.

Although science does not go into the details about the latter, it is still one

of the hidden, but important, driving forces behind scientific research.

During the years of my PhD work, I have built instruments, collected This is a generalintroduction only,for more detailed,scientificintroductions pleasesee the individualparts, each has itsown.

and analyzed data and tried to build a model around to be at least

self-consistent. In spite of all these endeavors, even if a model is self-

consistent, even if it also fits the experimental data and the numbers it

delivers appear to make sense, we shall never forget this thousands of

years old but still ever true message: "we are looking at nature through amirror".

Before going on, there is an important note:

I think science is not only about new discoveries and knowledge, but

it is also enlightening. It is an important part of being a scientist to en-

joy the sparks of possibly wild ideas, to see them emerge and of course

1 Bible, Joung’s literal translation, Job 28,20-21. and I.Corinthians 13,12.

1

2 Introduction

then sometimes see them being destroyed. This dynamics of ideas makes

science unique among most of the professions, and relates it closely to

art. In this thesis, I will make an attempt to reflect this duality of sci-

ence: both being some sort of loose, easy art, and being at the same time

rigorously precise and logical. Therefore I will deliberately use different

language styles in this thesis. My own thoughts, speculations and view

will be presented in a relaxed language style, while results and discus-

sions which are already published, or being submitted to journals - thus

having passed the rigorous logic and found to have a solid basis - will

be written in a formal style to emphasis their separation from specula-

tions, and freely floating ideas. This introduction is more an introduction

to the thesis itself, than an introduction to the science in it. The latter

will be given for each chapter separately, since they are so different, it

did not seem logical to have a single introduction split into several parts.

Many different questions are raised and discussed, and also three differ-

ent molecules are addressed, although mostly from a given viewpoint.

This common viewpoint is the perspective of the new optical method

developed during my PhD work. Therefore, this short introduction has

three goals:

• present the questions raised before and mostly during the work.

• present the structure of the thesis.

• and finally acknowledge all the the support I got during the years.

This thesis tries to summarize the results of the last couple of years in a

retrospective way. Looking backwards often yields a completely different

perspective, which may be somehow useful to better understand connec-

tions between pieces of a big puzzle. This case is not an exception, and

therefore, to show how the specific questions, goals were raised before

and also during the work, I will shortly “tell the story”: How the research

began, what did we expect, and how those ideas emerged, which now

form the basis of this thesis.

When I started my PhD-work under the supervision of Prof. Judit Fidy,This part of theintroduction is

mostly about thestory from my

personal perspective.

she just started a new project - in collaboration with Prof. Yonetani - with

human hemoglobin (HbA2). It was assigned as my PhD project. We did

not think then to develop a new method, rather it was our intention to

build upon the expertise already available in Prof. Fidy’s group in the

field of high resolution fluorescence spectroscopy, and pressure perturba-

tion methods, and use these techniques in a collaborative effort, to gain

2 Each abbreviation will appear in parenthesis when used for the first time.

Introduction 3

further insights into the mechanism of allosteric control in HbA.

During the long decades of experimental and theoretic work being done

on HbA many models have emerged to describe the phenomenon of oxy-

gen binding, and allostery. Most of these models are already parts of

basic biochemistry textbooks, and as such are considered as basic science.

However, many details are still not perfectly understood and described

by these methods, and the topic is still a field of active research. Just in-

cluding the last three years, over 23000 entries are found with a simple

search using the keyword “hemoglobin”, and while many of them ana-

lyze the genetic code behind diseases, there are also new papers about

structural insights of the molecule itself. This shows, that even today open

questions (and possible answers) regarding for example ligand migration

pathways [77] still exist. Prof Yonetani’s group is well known in the field

of hemoglobin, one of his most cited works publishes the new “global

allostery” model [155]. In this model the allosteric effectors (which are

small molecules, that can bind to HbA to modify its oxygen binding) are

proposed to bind to both oxygen-containing, and deoxygenated forms of

hemoglobin to modify the interaction between all of the monomers. Since

our special spectroscopic techniques are capable to somehow monitor

changes in this interaction, a collaboration was formed, and we started

to work with fluorescent hybrid HbA, in which two of the heme-groups

was exchanged to fluorescent porphyrin. Heme itself is non-fluorescent,

so this substitution was essential to open the way for the application

of our spectroscopic techniques. We have started with a pressure per-

turbation study, since pressure is known to influence interfaces between

molecules, and as such, it is perfect tool to study a tetramer such as

hemoglobin. We found that allosteric effectors modify the interaction be-

tween the two dimers in HbA in both oxygenation states, and also de-

termined the respective dissociation constants [117]. These findings sup-

ported the “global allostery” model.

The fluorescent porphyrins are perfect candidates also for high resolu-

tion fluorescence spectroscopy. A particular method used in our group is

fluorescence line narrowing spectroscopy (FLN ) which can be extended

with pressure perturbation to estimate the isothermal compressibility of

the protein [126]. In the case of HbA we have seen only a minuscule

change in the compressibility of the protein in most cases. This was sur-

prising to me, and seemed to be controversial to the fact that in the case of

the interfaces we did find a definite trend in the effect of these modifier

molecules. These FLN experiments were the first ones which pointed to-

wards the need of an optical method capable of monitoring slow, possibly

4 Introduction

ms timescale dynamical events. Since FLN is based on fluorescence emis-

sion, and requires very low temperatures (below 10K), it is not sensitive

to any type of dynamics which may not be activated at this temperature.

The only resolution to this controversy was then to assume that most of

the changes manifesting in the change of the interactions between sub-

units come from a type of dynamics to which the FLN-based method is

not sensitive. Taking into account that HbA is a fairly large molecule, I

had the idea that maybe its size is large enough to have its own “internal

universe” with slow, collective motions. And what if these motions are

the ones which are primarily influenced by the presence of various al-

losteric effectors? Could it be, that these are the motions that may play a

role in the control of the whole tetramer? Of course these were wild spec-Of course there aremethods, such as

NMR, to investigatethese effects, and

this is a very activearea of research,

with theever-increasing

capabilities of NMR,localized events can

also be monitored.

ulations, but triggered the question, that maybe using a different method,

which is sensitive to this time-range, it may show a more pronounced

difference between complexes of HbA and different allosteric effectors.

The fact, that the special mixed-metal Zinc-hybrids are not only fluores-

cent, but also phosphorescent, gave an instant push to try experiments

based of phosphorescence. Moreover, in the previous years I was using

phosphorescence spectroscopy during my diploma-thesis work in the de-

sign of a novel test method for antibiotic susceptibility [116, 115], so I

had quite a bit of experience in avoiding the usual pitfalls (controlling

different sources of quenching) associated with the method. The first ex-

periments quickly showed, that there is an interesting effect, however

to have reliable data, many instrumental developments had to be made.

The main difficulty arose from the fact that in these phosphorescence

experiments the signal level was extremely low: A typical experiment

had to run for about 3 weeks non-stop if no problems, such as power or

cooling water outages occurred. I had to build an automatic system (see

Appendix: Chapter A) to circumvent all these problems, and enable reli-This was the birth ofthe “departmental

legend”, that I wanta system which

acquires data while Iam on vacation,

maybe sailing. It ispartly true: It didacquire data also

during those times.

able non-stop data acquisition. These developments are not strictly part

of the scientific results, but indirectly still are: without the system built,

the data collection would not have been possible. The appendix to this

thesis describes these developments. This part is more about engineering

than science itself, therefore it is separated from the actual text of the

thesis.

I have used a special technique: I have deliberately not deoxygenated

the samples before freezing them, to have O2 molecules being trapped

inside the protein matrix, and I have avoided the use of glass-forming

substances, such as glycerol. Both turned out to be essential, and we haveobserved something, which was not seen before: The results from these temper-

Introduction 5

ature studies showed a phase transition in the average phosphorescence

lifetime, and we have shown that this can be interpreted in terms of an

activation of slow (ms - s timescale), global dynamics specific to HbA,

and distinct from the already well-known “glass-transition” observed in

glassy solutions of proteins. We have also shown that this dynamics is

sensitive to the presence of allosteric effectors, and with a simple theo-

retical model we could also calculate the energy and entropy change of

the system associated to the activation of this special dynamics. This was

also an answer to some of the questions raised before. Now, knowing

that with this new method - technique - we can calculate these interest-

ing parameters, it became an important question, if this is limited to the

special case of hybrid, fluorescent HbA, or is it maybe more general, and

applicable to other proteins as well? This was the time, when the wholeproject started to deviate from HbA, and we turned into the direction of slow,global dynamics of proteins in general.In a summer break I have asked my colleague Szabolcs Osváth, who then

worked with phosphoglycerate kinase (PGK) if he had some samples in

the fridge for me to run a test. He had several different constructs. It

turned out, that despite the signal levels being even lower than in the case

of HbA, a similar transition could be observed, and more experiments

then followed this initial one. We have shown, that indeed, inter-domain

communication in PGK does manifest in the transition. We have shown

that millisecond timescale inter-domain communication in PGK also existwithout the well-known “hinge-bending” motion. This is surprising, since it

shows that even if the boundary of the molecule is “fixed” (e.g., being

embedded in, and bound to a solid, such as ice in this case) important

motions, that may play a significant role in the function, still exist. Of

course this technique is not capable of providing structural details, but

the observed changes in the transitions may indicate that this specific

timescale of a few hundreds of microseconds to seconds may well be

very important in the function of enzymes.

At about this time Prof Fidy has started a new joint project with Prof.

Beáta Vértessy on the structural dynamics of dUTP-pyrophosphatase[11]

(DUT), and this new experimental method became part of the project.

DUT is known to be a homo-trimer, in which each of the three active

sites are built from parts of each three monomer. The whole structure

looking at it from the top resembles a triangle, in which each monomer

has a long “arm”, which reaches both other monomers, and the end of

this arm is one of the building parts of an active site. Prof Vértessy’s

group constructed a single-tryptohan (Trp) mutant of the protein, which

6 Introduction

was another perfect molecule for the new method. We have shown, that

the apo-enzyme behaves distinctly to the enzyme in complex with 2´-

deoxyuridine- 5´ - (a,b-imido) triphosphate (dUPNPP). The dynamics of

the “arm” region somewhat resembles the dynamics of the solvent in the

apo-enzyme, while it is close to the dynamics of a globular fold in the

complex with dUPNPP.

In this thesis the emphasis is laid on the new phosphorescence-based

method, and thus its structure is built around it:

part I : Demonstration of the method in the case of HbA.

• Description of the method and the theoretical model.

• Correlation with other results on HbA: measurement of the tetramer

dimer dissociation constant by pressure-perturbation method,

and estimation of changes in the isothermal compressibility mea-

sured by fluorescence line narrowing.

• Short summary.

part II : Application to other proteins:

• PGK - communication without hinge-bending.

• dUTPase - preliminary results on the dynamics of the arm region.

• General conclusions

After the bibliography, I have inserted an appendix, which is a descrip-

tion of the engineering work, and new instrumentation developed during

the research project. This is not strictly part of the thesis itself, but for the

engineering-oriented reader it contains some interesting additional de-

tails about the instrumentation and software I have developed during

the work.

Now, before the first part is started, I want to express my gratitude to

all of those, who participated in this exciting work. I am very grateful to

Prof Judit Fidy, my supervisor, for all of her support and patience she

had with me during the long years of work. She was not only an exciting

partner in discussions, and a very precise critic if it was the need for that

Introduction 7

3, but she also did everything to coach me to become a scientist. Without

all these years together, I would surely not enjoy science as much, as I do

now. I am also indebted to my colleagues, particularly to the whole “LSL”

group4, especially András Kaposi, Ferenc Tölgyesi (my diploma-thesis

supervisor), Levente Herényi, László Smeller and Szabolcs Osváth. The

“coffee-house meetings5” at lunchtime were fruitful times: I floated most

of the ideas during these informal conversations, many technical and ex-

perimental questions were answered, or we just simply had a great time

together. I have learnt the FLN technique together with Krisztián Szigeti,

we had a lot of fun, e.g., in the beginning when we desperately tried to

align the ring-laser for two days without success, and then András “gold-

handed” Kaposi just came by, and tweeked here and there a bit, and

whoila!... I am also grateful to Károly Módos who introduced me to the

Propeller microcontroller platform, which was then heavily used in the

instrumental developements. I am also very grateful to all of my other

colleagues, if I would list all the names, then I would need to list the staff

of the Department of Biophysics and Radiation Biology of Semmelweis

University in the last approximately ten years. I am fortunate to be part

of a great team - now lead by Prof. Miklós Kellermayer - built not only

of excellent scientists, but also great people and friends. Without their

constant support nothing presented in this thesis would have ever been

possible.

I am also grateful to my family, without their support and love I would

have never become a scientist, may God bless them with both of His

hands. I am also grateful to the Kapernaum Foundation, which is a Chris-

tian mission for children with multiple (mental and physical) disability.

The best ideas for my research always came during the days (and va-

cations) spent as a volunteer with them. After a week spent together I

always re-started work full of ideas and energy.

3 And it was in many cases. As the reader will see, I like to formulate ideas, specualtions,also in the cases when they are only based on limited data. While this is interesting, acheck needs to be kept on them.

4 Luminescence Spectroscopy Laboratroy5 © Csaba Böde, our former collegue. We always laughed the loudest, when he wanted

to work on something urgent. In other times, at the end of the day he told great storiesabout railways. We were all stunned that he knows the European railway time-table byheart...

Part I

D Y N A M I C A L T R A N S I T I O N I N H E M O G L O B I N

1T H E D Y N A M I C A L T R A N S I T I O N

1.1 introduction

The conformational dynamics of proteins is known to be extremely com-

plex phenomenon [56, 57]. It is a hierarchical network of specific mo-

tions across several orders of magnitude of spatial and temporal scales.

Some dynamic components are observable even at cryogenic tempera-

tures [158], whereas others become activated around the “glass transition

temperature” of proteins and the timescale may extend from picoseconds

to the time range of seconds [39, 97, 29, 27, 51, 108]. It is therefore experi-

mentally demanding to monitor a wider scale of these motions in a single

research approach [130, 16], since the various experimental and compu-

tational methods refer to specific time windows of motions. Most of the

results have been obtained on myoglobin, which has thus become “the

H-atom of biophysics” [40] due to its advantageous properties as a model

system [19]. The time-window of the applied methods in most cases was

far in the sub-millisecond range [55]. Motions involved in biologically rel-

evant reactions (e.g. domain motions, closure of loops), however, mostly

take place in the millisecond-second range. It is therefore of functional

significance to develop and utilize techniques that address this longer

timescale of protein dynamics [56, 33, 129, 15]. Although the functional

significance of conformational dynamics is becoming more and more

accepted[57], our understanding of its regulation and the exact mecha-

nisms of action in macromolecular interactions is far from complete[17].

Especially intriguing questions are related to the role of the protein en-

vironment in its internal fluctuations. These important questions may

involve coupling to the dynamics of the hydration layer, the bulk buffer,

the crowded environment of the cell, or to motions in any specific inter-

face bordering the molecule [41, 88, 156, 1, 79, 80, 47]. The answer must

be found for each time and amplitude scale of the involved motions. It

has been suggested, for example, that a strong coupling occurs between

the internal protein dynamics and fast fluctuations in the hydration shell,

whereas slower motions on a larger scale are slaved to fluctuations in the

bulk solvent [42]. The experimental techniques applied in the studies of-

ten involve optical measurements at cryogenic temperatures on samples

11

12 1.2 Methods

containing high percentages of glycerol. It is also relevant to investigate

how this circumstance may influence the conclusions concerning the dy-

namic coupling of protein and its environment. The following questions

were raised:

1. Is there a specific thermal activation of large-scale protein dynam-

ics in the time-window of a few tens of milliseconds up to a few

hundreds of milliseconds?

2. If yes, can this transition be described by the well-known theory of

“glass-transition”?

3. What is the significance of the protein environment, can the contri-

bution of the protein be separated from that of it’s environment?

To answer these questions we have developed a new optical method

based on phosphorescence lifetime detection, and an ideal model system

is one having in the molecule multiple suitable chromophores for spec-

troscopy. Therefore we have chosen a Zn-hybrid modified HbA, which

has 6 Trp residues in the tetramer, and two phosphorescent porphyrins

in its two b-subunits.

1.2 methods

1.2.1 Sample preparation

Sodium chloride, dimethyl sulfoxide (DMSO) and 4 - (2-hydroxyethyl) -

1 - piperazineethanesulfonic acid (HEPES) were purchased from Aldrich-

Sigma (St. Louis). All samples were prepared in 100 mM HEPES, pH 7.4

with double-distilled water. Hybrid human HbA with zinc-protoporphyrin

(Zn-PP) substituting the heme in the b subunits, [a-FeO2]2-[b-Zn]2-HbA

(Zn-HbA) was prepared in Takashi Yonetani’s Laboratory at the Univer-

sity of Pennsylvania [141] :

In short, HbA was prepared from human blood as described in [142]

according to the method of Drabkin [30]. HbA was promptly converted to

the carbonmonoxy-form (CO-HbA) and stripped of organic phosphates

by the method of Berman [14], and further purified by ion exchange chro-

matography. The final HbA solution was eluted in pH 7.4, 5 mM HEPES

buffer. The a and b subunits were isolated from CO-HbA, and the subunit

was converted to apoprotein by the acid-acetone method and then incu-

bated with Zn-PP to create b-zinc subunits. Finally, the a-Fe and b-zinc


Figure 1: Reference absorption spectrum of Zn-HbA.

350 400 450 500 550 600 650wavelength [nm]

abso

rban

ce [a

. u.]

subunits were mixed and incubated in the cold for 2 days. The (a-Fe-

CO)2-(b-Zn)2 form was then converted to the O2 bound (oxy-) form of

(a-Fe-O2)2-(b-Zn)2-HbA by strong illumination and a flow of pure oxy-

gen above the sample, which was kept on ice. Samples were transferred

to Budapest on dry ice and stored at -80°C until use after fast-freezing

in liquid nitrogen. Sample quality after thawing was controlled before

further experiments by recording an absorption spectrum, and overlay-

ing with the spectrum recorded on the fresh samples at the University of

Pennsylvania. Only samples with no detectable difference were used. The

control spectrum is shown in Figure 1. It can be seen, that the Zn-hybrid

has a well-defined absorption-peak in the Soret-region around 410 nm,

and also a structured Q-band around 550 nm. The position and shape of

the spectrum in these regions is very sensitive to structural changes in the

porphyrins themselves, and the protein matrix around them. This sensi-

tivity is a well-known, common feature of porphyrin-containing proteins

and is routinely used to control sample quality.

Human myoglobin (Mb) from Aldrich-Sigma was used as purchased.

The protein concentration was adjusted to 60 mM in all experiments.

We have also used Zn-PP, as a special case, deprived of the protein,

dissolved in DMSO. We have chosen this solvent, since Zn-PP has an

acceptable solubility in this medium, its polarity is not very far from

water, and it has no phase transition in the temperature range used in

these experiments.

14 1.2 Methods

1.2.2 Phosphorescence decay measurements at various temperatures.

The conclusions in this chapter are based on phosphorescence lifetime

data obtained on samples in thermal equilibrium, at various tempera-

tures, starting upwards from 8 K. The samples were equilibrated for 4

hours at 8 K before starting the heating cycle to ensure thermodynamic

equilibrium. Then temperature was changed in 5 or 10 K increments, and

the samples were equilibrated at the target temperature for 45 minutes

before the start of the phosphorescence decay measurement. At each tem-

perature the triplet state lifetimes of the chromophores, namely Zn-PP,

palladium coproporphyrin (Pd-CP) or Trp-s of the proteins were mea-

sured using the time-domain mode of an EAI CD900 spectrometer (Edin-

burgh Analytical Instruments, Edinburgh, U.K.) equipped with a mF900

Xe flash lamp of an energy of approximately 1 mJ/pulse and a pulse

width of 2 ms FWHM (full width at half maximum). Excitation and emis-

sion wavelengths were 409, 384 or 290 nm and 723, 668 or 421 nm (for Zn-

PP, Pd-CP and Trp, respectively), with 5 nm bandpass. The phosphores-

cence emission was very weak due to strong light scattering and quench-

ing effects. To reach an acceptable signal/noise ratio for evaluation, up

to14 000 consecutive flashes were summed with a time resolution of 80 ms.

The long data collection time involved the possibility of photobleaching,

which was controlled by repeated data collection periods and lifetime

evaluation. Consecutive decays showed no detectable difference in signal

intensity, and the shape of the emission spectrum also did not change.

This confirms that no significant photobleaching was caused by the long

data-collection. Phosphorescence photons were detected by a photomulti-

plier tube (R928, Hamamatsu Photonics, Shimokanzo, Japan) operated in

single photon counting mode, and cooled to 255 K (C65972 water-cooled,

Peltier operated PMT-cooler). After amplification, data were collected by

a Norland 5000 multichannel analyzer card (Viking Instruments, Madi-

son, U.S.A), and a custom-made multiscaler, controlled by an integrated

data-acquisition software, which I have developed. The software also con-

trolled the cryostat, used for adjusting the temperature of the sample,

and the safety subsystem responsible for protection against power and

cooling-water outages. The system is described in detail in appendix A

of the thesis.


1.2.3 Evaluation of phosphorescence decay curves

The experimental goal was to characterize the dynamic state of the se-

lected protein at various temperatures by the phosphorescence lifetime

of a specific embedded chromophore. This parameter of chromophores

in an ensemble of protein molecules representing also an ensemble of

dynamic conditions is considered heterogeneous since both the heteroge-

neous conformational environment and the heterogeneity of the quench-

ing conditions affect the individual lifetimes. We used the average life-

time of the heterogeneous lifetime-population as a dynamic parameter.

Two approaches have been applied to determine reliable average life-

times. We analyzed the decay curves by the method of Maximum Entropy

(MEM) yielding lifetime distributions and fitted the decay data (I(t) func-

tions) with the sum of exponential decay functions of discrete lifetime

values:

I(t) =n

∑i=1

Ai e−t/τi (1)

where Ai and ti are the amplitudes and lifetimes of the individual com-

ponents, respectively, and n is the number of exponentials used for the fit-

ting. According to our experience, an acceptable least squares fit required

3 ... 5 discrete exponentials. The ensemble average <t> was taken into con-

sideration, since this is the parameter, which can be also approximated

with the help of a simple thermodynamic model. The correct average

can be calculated as a weighted average of the individual lifetime values,

since the photon-statistics from every homogeneous sub-population with

a given ti lifetime follows an exponential function. Let the probability of

a photon being emitted at time t be :

P(emission at time t) ∼ Ai · e−tτi (2)

The total number of photons emitted from this population is thus:

Ni =

∞∫0

Ai · e−tτi dt = Aiτi (3)

Thus, the weighting factor in the summation for each ti is Ni = Aiti.The average lifetime can then be expressed as:

< τ >=

n∑

i=1Niτi

n∑

i=1Ni

=

n∑

i=1Aiτ

2i

n∑

i=1Aiτi

(4)

16 1.2 Methods

Table 1: Parameters of the selected discrete exponential fittings. The remarksshow the classification of the lifetimes as well. The lifetimes below 0.2ms are arising from the 80μs sampling time-quantization, and were dis-carded from further analysis, therefore these are not shown in the table,but are shown in Figure 2.

77 K 215 K 235 K

t amplitude t amplitude t amplitude

[ms] [a.u.] [ms] [a.u.] [ms] [a.u.] remark

0.9 8746

0.2 14941 0.6 17502 instrument response

2.0 18741 2.2 61590 strongly quenched

5.7 5604 6.3 39639 4.0 37911 medium quenched

23.6 41042 15.9 35777 10.1 7068

long lifetime35.0 22805 31.3 6206 25.6 1379

The <t> values also represent the ensemble average: if every single

state had been resolved, then Ai values would represent the number of

molecules in the i-th state, having a lifetime of ti, and the summation

would be over the whole ensemble, thus n would be the number of dy-

namic states. This value is then approximated by Equation (4) , where

the individual lifetime values are either determined by the discrete expo-

nential fitting method, or by the Maximum Entropy Method[20] (MEM).

MEM inversions were obtained by importing the data into a custom-

made program (by Károly Módos) for the analysis of dynamic light scat-

tering data. In the case of the calculation of <t> from MEM-data, the

summation is over the whole discretized lifetime distribution.

Based on repeated lifetime acquisitions and different methods of cal-

culation of <t> values1, the relative error in all experiments was less

than 5%, except for the Trp, where the signal level was very low due to

strong quenching and energy-transfer to the heme-groups. In the case

of Trp data the relative error of the average lifetime values was 5 ... 15%.

Sample decay curves are shown in Figure 2 together with the correspond-

ing MEM-derived lifetime distributions. It can be seen, that the discrete-

exponential method provides a very good fit to the data, the error func-

tions do not show any residual structure, and the lifetimes match the cor-

responding MEM curve. In the case of the Trp data the signal/noise ratio

1 Comparison yielded a difference between MEM-based average values and discreteexponential-based ones of less than 5%. Also the difference between average lifetimevalues between two <t>-s of individual lifetime data is less than 5%


Figure 2: Sample decay curves of Zn-HbA at various temperatures. The fittedcurve is shown in red, the result of the MEM is shown on the righttogether with the lifetime and relative weight of the discrete exponen-tials.

0 50 100 150 200 250 300 350 400 4501

10

100

1000

10000

100000

-1012

0 50 100 150 200 250 300 350 400 4501

10

100

1000

10000

100000

-1012

0 50 100 150 200 250 300 350 400 4501

10

100

1000

10000

-2024

time [ms]

time [ms]

time [ms]

phos

phor

esce

nce

int.

[a.u

.]ph

osph

ores

cenc

e in

t. [a

.u.]

phos

phor

esce

nce

int.

[a.u

.]re

l.err.

rel.e

rr.re

l.err.

0.01 0.1 1 10 100

77K <τ >

MEM = 28.5 ms

<τ >MultiEXP.

= 28.4 ms

0.01 0.1 1 10 100

τ [ms]

τ [ms]

0.01 0.1 1 10 100τ [ms]

rel.f

requ

ency

rel.f

requ

ency

rel.f

requ

ency

215K <τ >

MEM = 16.8 ms

<τ >MultiEXP.

= 16.0 ms

235K <τ >

MEM = 5.1 ms

<τ >MultiEXP.

= 6.4 ms

18 1.2 Methods

was too low, to obtain a reliable MEM inversion, however the discrete

exponential fitting was still stable. Therefore, to maintain consistency we

have used the <t> based on the latter calculation for further analysis.

The results of the multiple discrete-exponentials fitting is presented in

Table 1. The shortest lifetime is marked “instrument response” since it

is still influenced by the sampling method, but we decided to include it

in the analysis. It can also be seen, that all lifetime components show a

decrease with increasing temperature, and the maxima of the amplitudes

shift to shorter lifetimes.

1.2.4 Adjusting the temperature of the sample

The adjustment of the initial low temperature of the sample and of the

higher temperatures was done by using a Cryophysics M22 type closed

cycle Helium refrigerator (Cryophysics SA, Geneva, Switzerland) and

Lake Shore M330 temperature controller (Lake Shore Inc. Westerville,

USA). The cryostat was also controlled by the integrated data-acquisition

software. Using the cryostat, its cold finger of copper must be brought

into and kept in good thermal contact also under vacuum conditions.

The sample of 80 ml volume was contained in a quartz (UV fused silica)

tube of 2.7 mm inner diameter, sealed gas-tight with a conical Teflon stop-

per. The techniques required for this study had to achieve the following

conditions:

1. to bring the sample to 8 K fast enough to avoid phase separation

and bulk crystallization of the aqueous sample

2. to maintain the thermal contact of sample and cold finger in a broad

temperature range from 8 K up to 273 K.

3. reproducibility of the structural conditions in the sample.

These conditions had to be tested as thoroughly and rigorously as possi-

ble.

cooling to 8 k . Fast cooling was achieved by using a copper adapter

attached to the cold finger prepared with an indium coated hole that con-

tained the sample tube with a tight fit. Prior to the insertion of the sample,

the copper housing was pre-cooled to 77 K by liquid nitrogen. The posi-

tioning of the sample in the cryostat was fast and the low temperature

of the housing promoted fast cooling, moreover the sample could also


be pre-cooled to 77 K by liquid nitrogen prior to insertion into the hous-

ing as well. The data obtained by this method, however, showed that the

good thermal contact between the sample tube and cold finger could not

be reliably maintained at higher temperatures (> 200 K ) due to the dif-

ferent thermal expansion of copper and quartz. This method was useful,

however, as a control, since it provides an extremely rapid cooling, and it

is also the same cooling method used routinely in biochemistry to safely

store proteins avoiding structural damage or alteration.

maintaining the thermal contact of sample-tube and cold

finger in a broad temperature range . I have designed an-

other copper adapter fixing the contact of the sample-tube and the cold

finger. This sample holder consisted of two parts, an indium-coated part

was fixed to the cold-finger of the cryostat, and a second part was mounted

to it with screws. The quartz tube was inserted between these two parts,

and springs were used to firmly press the tube to the indium coating.

This design finally achieved the good thermal contact in the full tempera-

ture range of the experiments. In this method, however, the positioning of

the sample in the cryostat required more time than to just put it in a hole,

thus pre-cooling to 77 K made no sense2. The cold finger in this method

was first pre-cooled to 240 K by the cryostat. At this temperature the tube

was fixed, the cryostat closed, evacuated and continued cooling to 8 K by

the highest cooling rate. Phosphorescence lifetime data were determined

at various increasing temperatures starting from 8 K on samples cooled

either by the “fast cooling” method (with pre-cooling to 77 K) or by the

second method (with pre-cooling to 240 K) for comparison. The data

showed identical temperature dependence in the two cases if the temper-

ature stayed below approximately 230 K, as shown in Figure 3. It can be

seen, that up to 200 K the two curves overlap perfectly, but above that

moderate deviations start to appear. These deviations were sometimes

larger than shown in Figure 3, due to the instability of the contact be-

tween the quartz tube and the copper sample holder. The perfect overlap

up to 200 K, however, could always be reproduced. The absolute errors of

the <t> values are also shown in Figure 3, and it can be seen that the size

of the error-bars are comparable to the symbol sizes. To avoid cluttering

2 Since the cryostat has to be open during the positioning of the sample, humidity in theair, and also other substances may freeze onto the surfaces at 77K. This “snow” latercauses a failure in reaching temperatures below 30K, and also a severe degradation ofthe transparency of the cuvette. Therefore if the cryostat has to be open for more than afew seconds, it can not be cooled to 77K, but only to around 240K.

20 1.2 Methods

Figure 3: a: Comparison of the average lifetime (<τ>) values for Zn-HbA mea-sured using the two different protocols: “fast cooling” (red) and ex-treme rapid cooling (grey). A cooling path (returning from 230 K) isshown in black. The error bars indicate the estimated absolute error ofthe <τ> values.b: Comparison of the <τ> values of fast cooling protocol (red curve,and red axis) and deliberately slow cooling protocol (brown curve andaxis). The error bars indicate the estimated absolute error of the <τ>values.

100 120 140 160 180 200 220 240 260 280 3000

5

10

15

20

25

0

5

10

15

20

25

30

35

temperature [K]

<τ>

[ms]

0 20 40 60 80 100 120 140 160 180 200 220 240 2600

5

10

15

20

25

30

35

temperature [K]

<τ>

[ms]

a

b


of the graphics, I will only show error-bars if the relative error is more

than 5% (typically in the case of Trp data). Based on the results of this

control study, we selected the second method for cooling protocol in the

reported experiments and considered it a “fast cooling” technique. We

found that the results obtained by this protocol were reliable within the

whole temperature range of the studies.

1.2.5 Further control experiments

Since I was developing a new method, it was essential to make careful

control experiments, to verify sample quality, repeatability of the exper-

imental conditions, etc. The most important control experiments we de-

signed are outlined below.

reproducibility-reversibility. In the experiments we detected Of coursereversibility is onlyexpected if there isno phase-transition(the secondtransitioncorresponds to thesolid to liquid phasetransition of thebulk solvent) in thebulk solvent. If yes,then aninverse-directionaltemperature scan by5K steps would bevery different thanthe fast-cooling, andtherefore would notyield the sameresults.

phosphorescence lifetime data under thermally activated quenching con-

ditions. The quenched emission signal at higher temperatures (above 200

K) was very week and thus long data collection times were needed. A

total measurement time covering the whole temperature range spanned

over several days up to a week, sometimes even longer. Still, parallel

experiments involving larger steps on the temperature scale3 were per-

formed and proved the reproducibility of the data. Besides reproducibil-

ity, we found also complete reversibility of the temperature effect (as can

be seen in Figure 3, black points) on the phosphorescence lifetime if the

temperature did not exceed 230 K. This experience showed that the se-

lected time period of thermal equilibration at each temperature ( 45 min)

was sufficient in our temperature dependence protocol. Since the struc-

ture of the cold sample is crucial in such an experiment we controlled the

effect of the cooling rate also by using a deliberately slow cooling method.

In this method the sample was gradually cooled from 270 K to 8 K during

five hours. From 8 K, the sample was then heated stepwise to 270 K the

same way as with the method used regularly, and phosphorescence decay

curves were measured. Figure 3also shows the average phosphorescence

lifetimes calculated from these decays (brown line). It is apparent, that be-

sides the lifetime being altered, the two-step behavior is also missing in

this curve: it starts to decline from the long lifetime plateau of the cryo-

3 At some randomly selected temperature points two or more decay curves were taken,and fitted individually. This provided a measure both for the relative error of the lifetimedetermination, and for the repeatability of the decay curves. It also served as a control torule out possible photobleaching or sample degradation.

22 1.2 Methods

genic range at a higher temperature than in the case of the fast-cooled

sample. We found that in the samples prepared in this slow cooling pro-

tocol, precipitates were also formed. This shows that if the cooling rate

is not sufficiently fast, the structure of the solidified sample is most prob-

ably inhomogeneous, and this condition leads to partial denaturation.4

This could partly arise from freeze-concentration, which can be signifi-

cant if the cooling rate is slow. The striking difference of the this curve

and the curves corresponding to the two other cooling methods shows

that by a sufficiently rapid cooling method these effects can be avoided.Above a certaincooling rate it seemsthat sample quality

is not affected.absorption spectroscopy It is accepted that the optical absorp-

tion spectrum of the heme in heme proteins is a sensitive monitor of

deterioration or alteration of the protein structure around the heme. In

Figure 4 we show the control of the cooling effect based on absorption

spectroscopy. Spectra of Zn-HbA are shown at room temperature under

three conditions: the spectrum before the experiment (black curve), the

spectrum after the usual cooling-warming cycle protocol of our lifetime

experiments (green curve), and the spectrum after the slow cooling pro-

tocol (red curve). It is seen and evident from the difference absorption

curve (50x magn., grey dashed line) that the usual cooling protocol did

not change the environment of the Zn-porphyrins in the protein. The

slow cooling protocol caused protein precipitation, and also a distorted

absorption spectrum after the cycle as shown in the figure. This further

confirms that the fast cooling protocol, which was used can be considered

“safe” for the protein.

control for the protein concentration possibly affected

by freezing It is well known, that by cooling a solution the effect of

freeze-concentration may have an important role. In these experiments

it is essential to estimate this effect as well. For this test we have chosen

4 If we consider our interpretation of the lifetime data (see in the discussion: quenching dueto the activation of collective dynamics of the protein), then this lack of the first step isconsistent with the denaturation of the protein: The deterioration of the protein structureprobably eliminates the structural cavities of the intact structure, the places where oxygencan be trapped [136, 25]. If these cavities are lost, the oxygen content of the proteinmatrix would be largely reduced, and collisional quenching with oxygen molecules willonly occur if they are allowed to enter the matrix from the bulk solvent. This becomessignificant only when the mobility in the bulk phase is sufficiently increased, whichcorresponds to the second step in the temperature profile. Indeed, the quenching in thedeteriorated sample starts to occur in this temperature range. This consideration furthersupports our interpretation of the lifetime data, that is, these oxygen molecules may playimportant role in the quenching effect under intact conditions.


Figure 4: Absorption spectra of Zn-HbA. Freshly thawn Zn-HbA is shown inblack (identical to Figure 1) and after an experiment involving the fastcooling technique (green curve) together with the difference spectrumat 50x magnification (grey dotted line). Spectrum taken after the de-liberately slow cooling technique is shown in red. Curves are shiftedalong the absorbance axis for clarity.

250 300 350 400 450 500 550 600 650 700

wavelengh [nm]

abso

rban

ce [a

.u.]

24 1.3 Results of the dynamical transition

the recombinant Trp mutant forms of yeast Phosphoglycerate Kinase [95].

We performed the same thermally activated phosphorescence quenching

studies on protein solutions of 20 µmolar concentration by the fast cool-

ing protocol. It is known that this protein precipitates above 40 µmolar

concentration, thus any significant freeze-concentration would case pre-

cipitation. We did not observe any precipitation after the thermal cycle.

This shows, that while freeze-concentration can not be totally excluded,

the protein is surely not concentrated by more than a factor of 2 during

the cooling process.

the oxygen content of the samples In most experiments, the

protein solutions were saturated with the oxygen of air by carefully and

slowly bubbling air into the samples for 5 minutes prior to the experi-

ment. However, according to our hypothesis (as discussed later) the O2

molecules embedded in the system play an important role in the ob-

served effect. Therefore it was important to design a “negative control”,

i.e. significantly decrease the O2 content of the samples. The goal was to

achieve partial oxygen saturation without inducing structural changes in

the protein. These partially oxygen-saturated Zn-HbA samples were pre-

pared using a special procedure: As a first step, the temperature of the

unsealed sample (in air-saturated form) was rapidly decreased to 250 K.

At this temperature, the pressure was reduced to 10-2 mbar, and this low

pressure was maintained for ½ hour. Subsequently, the sample was sealed

and further cooled to 8 K. The measurements were then carried out start-

ing from this state like those performed with oxygen-saturated samples.

Possible denaturation or change in the redox state of the heme during

experiments were controlled by recording the absorption spectrum. No

significant changes were detected in the 270-700 nm wavelength range

after the thermal cycles, or after partial deoxygenation.

1.3 results of the dynamical transition

In this section I will summarize the first group of results obtained by the

new phosphorescence quenching method.

1.3.1 Phosphorescence lifetime of Zn-PP in HbA as a function of temperature

The intrinsic phosphorescence lifetime of Trp has been suggested for and

successfully applied to monitoring the internal dynamics of proteins at


room temperature [45]. Since molecular oxygen is a very effective colli-

sional quencher of phosphorescence [145], these studies have been always

performed in the absence of oxygen. In this new method I have decided to

- instead of deoxygenation - saturate the samples with air (oxygen) and

register the phosphorescence lifetime in thermal equilibrium at various

temperatures starting from 10 K up to 273 K, to detect the activation of

quenching effects. The chromophores were Zn-PP, substituting the heme

in the ß subunits of Zn-HbA and the tryptophans of the protein. In low

temperature optical studies transparency is usually maintained by the

addition of cryosolvent. I wanted to refrain from changing the physical

parameters of the sample (protein and solvent), and therefore avoided

this method. Figure 2 shows examples of phosphorescence decay data

of Zn-PP in Zn-HbA on a semi-logarithmic plot at various temperatures,

the decay curves arising from discrete fittings (see Equation (1)) and the

error of the fittings. Although the signal was low due to significant light

scattering, with sufficient data collection time, acceptable signal/noise

levels could be reached even at higher temperatures, where quenching ef-

fects became activated. The discrete lifetime components, the correspond-

ing amplitudes and the <t> values are shown in Table 1. The phospho-

rescence decay data were also evaluated by MEM. The two approaches

yielded results with remarkably good agreement, the ensemble average

lifetime values calculated by Equation (4) in both cases agreed very well,

and followed the same trend in function of temperature, as can be seen in

Figure 2. Lifetime components of 100 ms range appeared in both methods

of evaluation. Based on the analysis of the instrument response function

and on the fact that the phosphorescence decay was recorded with 80

ms resolution, these were considered as experimental artifacts and were

omitted from data evaluation. The next shortest component in both ap-

proaches was in the lifetime range of 0.9 ... 5 ms. This component - of

low population at lower temperatures - seemed unaffected by the tem-

perature, and remained almost the sole component close to 273 K. We

attributed this signal to such chromophores which have trapped oxygen

molecules in their immediate vicinity of specific configurations. These

chromophores are expected to be significantly and strongly quenched, as

the trapping of oxygen molecules in the vicinity acts as a seemingly high

quencher concentration[31]:

τ0

τ= 1 + KSV [Q] =

F0

FKSV = kqτ0 kq ∼ D (5)

In Equation (5), the Stern-Volmer equation, the lifetime (t) and the emis-

sion intensity (F) of a given chromophore under different quenching con-


ditions is given (t0 and F0 are the values without quenching). [Q] is the

quencher (mostly O2) concentration, and KSV is the dynamic quenching

constant, which is proportional to - among several other factors - the

diffusion coefficient (D) of the quencher in the matrix around the chro-

mophore. It can be seen, that if either [Q], or D change, both cause a

change in t. Trapping of O2around the chromophore may act primarily

as an increase in [Q]. The trapping may further cause modified diffusion

(D) of the oxygen, which can then also contribute to further increase of

the quenching efficiency by increasing the quenching rate (kq). The Stern-

Volmer equation is originally expressed for a single chromophore, but

can be extended to population averages as well, then instead of a single

t we take the population average <t> , and of course then all the other

parameters are population averages as well (<KSV> , <D> , etc.)

The normalized average lifetime of Zn-PP in Zn-HbA as a function of

temperature is shown in Figure 3. The lifetime does not change signifi-

cantly from 10 K up to about 180 K, thus in this temperature range there

is no significant change in the quenching process as well. Above this tem-

perature, additional quenching effects become activated and the lifetime

drops in two markedly separated steps on the temperature scale. The first

step begins at around 190 K and becomes complete at around 230 ... 235

K. The second step follows the first one and completely eliminates the

signal5. Importantly, the phenomenon is fully reversible along a cooling

path if reverted below 250 K – an example is also shown in the figure (a:

black triangles).

Evidently, this stepwise behavior of the average lifetime vs. tempera-

ture graphs shows two transitions in the quenching process. Both transi-

tions arise from the fact that dynamic quenching is changed, becoming

more and more activated. The nature, origin of these dynamic activations

are different in the two cases, however.

5 At least, the signal is not detectable with the instrument used in these experiments. Sincethe drop of the lifetime is accompanied by a drop in the intensity (F) as well, accordingto the Stern-Volmer equation, if the quenching constant is increased, after a certain pointthe signal level will drop below the detectable level. Of course theoretically this is nota complete elimination of the signal, but technically it is. Therefore on the graphs I willshow a lifetime of 0 in these cases, to indicate this fact.


Table 2: <τ> data of the chromophores at 10K temperature.

sample <t> ± s.d. at 10K [ms]

Zn-PP in HbA 28.7 ± 0.6

Trp in HbA 212 ± 22

Trp in Mb 605 ± 44

Pd-CP in HEPES 2.14 ± 0.11

Zn-PP in DMSO, at 100 K 0.11 ± 0.05

1.3.2 Mechanisms underlying the two steps of phosphorescence quenching ofZn-HbA

To examine the contribution of the protein matrix to dynamic activa-

tion, the phosphorescence lifetime measurement was also performed on

a chromophore sample deprived of the protein. Because the solubility of

Zn-PP is extremely poor in aqueous buffer, we measured the emission

of Pd-coproporphyrin (Pd-CP) instead under buffer conditions identical

with those of the protein samples. Pd-CP is a porphyrin very similar to

Zn-PP, only a few atoms differ in the two structures. But Pd-CP’s phos-

phorescence emission is much stronger, partly due to the well-known

heavy-atom effect [54, 7]6. Based on literature data from NMR studies

on the thermal activation of the mobility of protons coordinated to buffer

components in aqueous solutions[138], referring to the same temperature

range as in our experiments (discussed below), it can be supposed that

the structural coupling of the Zn- or Pd-porphyrin derivatives to the sol-

vent matrix cannot be significantly different. Data starting from 120 K

are shown in Figure 5 (blue curve). For comparison, the data for Zn-HbA

are also included (red curve), all data are normalized, and error bars are

omitted for clarity. The data were fitted with two sigmoidal functions From all figures,where the error barsizes are comparableto the symbol size,the error bars areomitted for clarity.

based on a simple thermodynamic model (see later) in the case of the

first transition, and a simple sigmoidal curve for the second transition.

To better characterize the two steps in the quenching effect, the negative

derivative functions of the fitted curves are also presented. The data are

normalized for better comparison, the absolute <t> values are listed in

Table 2.

In the case of Pd-CP, in the low temperature range, a gradual and slight

quenching effect appears to be activated. Then, well above the tempera-

6 It is known that when heavy atoms (high atom number) are included in aromatic systems,the phosphorescence efficiency generally greatly increases.


Figure 5: Normalized average phosphorescence lifetime values of Zn-HbA (redcurve) and Pd-CP (blue curve). The negative derivative functions arealso shown. The lines are fitted functions to the original data shownwith symbols. (Our own model function to the first transition and asigmoid curve to the second)

120 140 160 180 200 220 240 260 280 300

temperature [K]

0

1

norm

alize

d av

erag

e life

time

−Δ ⟨τ ⟩ΔT


Figure 6: Normalized average lifetime data of Zn-PP in DMSO (green line andsymbols). For comparison Zn-HbA data is also shown (red curve).

100 150 200 250 3000

1

temperature [K]

norm

alize

d av

erag

e life

time

ture range of the first quenching step in Zn-HbA, a slight step is de-

tected at around 240 K. At approximately 265 K, near the melting point

of ice, almost complete quenching occurs. The slight quenching step at

around 240 K is comparable with results of proton NMR relaxation ex-

periments in the 500 µs time range, and is attributed to the activation of

hydrogen motions in structured water regions around the components

of aqueous buffers [138, 137]. Thus we identify this step with the mo-

bilization of structured water around the porphyrin molecules and the

buffer components. This mobilization can be accounted for the increase

in the diffusion coefficient of quenchers, and thus for the decrease in life-

time. The quenching experiment was also performed on Zn-PP dissolved

in DMSO, the result is strikingly different, as shown in Figure 6. This

solvent was selected because it does not have any phase transition in the

studied temperature range. Although the intrinsic lifetime was strongly

quenched by the sulfur of DMSO (as can be seen in the extremely short

lifetime value in Table 2), the signal was measurable up to 274 K. A grad-

ual quenching effect without any steps was observed corresponding to a

matrix without a phase transition in the studied range. This also shows,

that without the protein matrix, the low-temperature (first) step observed

in the quenching experiment with Zn-HbA is absent. Comparison with

NMR data suggests that when the dynamics of the matrix (protons of the


Figure 7: Normalized average lifetime data of partly deoxygenated Zn-HbA (or-ange curve, triangles). For comparison the curves of normal Zn-HbA(red) and Pd-CP (blue) are also shown.

0

1no

rmali

zed

aver

age

lifetim

e

120 140 160 180 200 220 240 260 280 300temperature [K]

−Δ ⟨τ ⟩ΔT

hydration layer) coordinated to a molecule dissolved in aqueous solution

(i.e. one chromophore) becomes activated, a phosphorescence quenching

effect may be observed. Therefore we conclude that the low-temperature

step in the quenching experiment on Zn-HbA should be attributed to the

activation of motions in the protein matrix around the chromophore. The

NMR data also suggest that the second step in the HbA data, which over-

laps with the transitions seen in the data of Pd-CP in HEPES correlates

with the activation of the hydration layer around the protein.

1.3.2.1 The role of collisions with O2 molecules in the quenching effect.

The role of collisions with O2 molecules in the quenching effect can be

studied by comparing the data obtained on the fully air-saturated sample

with those of the partially deoxygenated sample in the case of Zn-HbA,

as shown in Figure 7. The comparison indicates that partial depletion al-


most completely eliminates the low-temperature quenching step7, while

the second step remains detectable. It has to be noted however, that the

very small remains of the first step still occur at the same temperature

as in the O2-rich samples. It is also important, that in this sample, totalquenching occurs only around the thawing temperature of ice. These observa-

tions show not only that the low-temperature step detected in oxygen

saturated protein samples is related to activated motions in the protein,

but also that these motions are permissive of oxygen diffusion. In both

the protein and the aqueous matrix, the diffusion of oxygen requires the

activation of large-scale motions[39, 157]. The results indicate that the ac-tivation temperature of such motions of the protein (possibly forming a unifieddynamic unit with its hydration layer) and of the matrix are clearly distinguish-able, and that of the protein is lower.

1.3.2.2 Activation of millisecond motions in the protein and in the solvent maynot be separated in the presence of glycerol.

It has been suggested that large scale motions - e.g. those allowing for a

“hopping”-like movement of small molecules in the surrounding matrix,

or allowing the uptake or release of such ligands – are “slaved” to two

kinds of fluctuations around the protein matrix: to the a-fluctuations in

the solvent environment through long-range dipole-dipole interactions,

while their internal local vibrations follow the behavior of the b-fluctuations

of their hydration shell[35]. The experimental techniques underlying these

models often involved optical spectroscopy at low temperature using the

standard method of adding cryosolvent (glycerol) in quite high percent-

ages (up to even 90%) to the aqueous buffer of the protein solution to

avoid light scattering, to extend the measurable range of kinetic parame-

ters, and to avoid the possible structural effects of crystalline ice forma-

tion during cooling. To test the effect of cryosolvents, the phosphores-

cence quenching experiment was repeated on Zn-HbA in the presence of

60% (v/v) glycerol as shown in Figure 8. Glycerol changes both quench-

ing steps, shifting their characteristic temperature ranges closer to each

other. The increase in the temperature of the first step (from 213 K to 220

K) we attribute to the effect of increased viscosity on protein dynamics

[3]. The lowered temperature of the second step (to 240 K) is compara-

ble to the phase transition point of concentrated glycerol/water mixtures

(-34.7 °C ≈ 238 K for 60% (w/w) glycerol content). The two-step fea-

7 The derivative curves are normalized to their area under the curve. Without this normal-ization the derivative curve of the partially deoxygenated sample would not be seen inthe common figure.


Figure 8: Normalized average lifetime of Zn-HbA in 60% v/v glycerol mixture(black symbols and curves). For comparison Zn-HbA under the usualconditions is also shown with red.

0

1no

rmali

zed

aver

age

lifetim

e

120 140 160 180 200 220 240 260 280 300

temperature [K]

ture of the quenching effect becomes observable only in the derivative

representation, whereas in the lifetime vs. temperature function, the two

steps fuse into a single step, easily attributable to the activation of mo-

tions in the solvent, which is of glassy nature in the case of high glyc-

erol content. In such a case the slaving of large-scale protein dynamics

to a-fluctuations of the solvent above Tg[34] 8 (now ~ 210 K) may be a

good approximation, since the Tg value of the protein and that of the

glassy solvent almost overlap with each other. The relation of protein dy-namics and solvent dynamics remains hidden under these conditions. There is

another important outcome of the glycerol effect: the shift of the activa-

tion temperature of protein dynamics directly proves that it is sensitive

to the structure and the dynamic nature of its immediate environment.

The ability of high glycerol concentrations (>65%) to cause even protein

denaturation (as can be observed in several cases, although not always,

8 Tg is the glass-transition temperature. Should the observed effect be a glass-transitionsimilar to the a- and b-fluctuations described in the cited articles, then Tg in our caseshould be the transition temperature, approximately 210 K.


and some proteins are less sensitive than others) is another point which

should not be overlooked.

1.3.2.3 The same protein dynamics is observed either by porphyrin or by tryp-tophan phosphorescence.

To prove that the observed dynamics monitored by Zn-PP in the ß sub-

units is not the property of the heme environment, but is characteris-

tic of the whole protein, I have measured the dynamics activation also

based on the Trp phosphorescence of Zn-HbA. The protein contains six

Trp residues. The Trp lifetimes were relatively short[80] even at low tem-

peratures (see Table 2) due to self-quenching and energy transfer to the

hemes[117], but could be determined with acceptable precision. The Trp

Figure 9: Normalized average lifetime of the Trp residues in Zn-HbA (blue curveand symbols). The error is also shown, since it is larger than 5%. Forcomparison the data of Zn-PP in Zn-HbA is also shown (red curves).

0

1

norm

aliz

ed a

vera

ge li

fetim

e

120 140 160 180 200 220 240 260 280 300temperature [K]

−Δ ⟨τ ⟩ΔT

lifetime data compared with the data of Zn-PP are shown in Figure 9.

both first quenching steps are very similar in the two kinds of monitoring,

indicating that the effect reflects the global behavior of the Zn-HbA ma-

trix. The perfect overlap in the temperature scale proves, that the dynamical acti-vation of the protein matrix is not a local phenomenon around the chromophores,but instead a dynamical transition of the whole protein molecule. The differ-

ences in the step sizes are caused by differences in the oxygen diffusion


Figure 10: Normalized average lifetime of Myoglobin (dark green line and sym-bols). For comparison the Trp data of Zn-HbA is also shown. Forclarity only the error bars of Mb data are shown on the graph.

0

1no

rmali

zed

aver

age

lifetim

e

120 140 160 180 200 220 240 260 280 300

temperature [K]

−Δ ⟨τ ⟩ΔT

pathways in the protein matrix to the site of the different chromophores

(heme or Trp), and differences in the quenching efficiency as well.

1.3.2.4 The first quenching step is specific for the protein.

The use of Trp phosphorescence allowed us to compare the phosphores-

cence quenching effect in two different proteins. We selected human Mb

having two Trp-s for comparison, dissolved in the same buffer as HbA.

The first phase of lifetime decrease is significantly different in the two

distinct proteins, whereas the second quenching step becomes activated

at nearly identical temperatures for both proteins as can be seen in Fig-

ure 10. Thus, the first step in the thermal activation of quenching is character-istic and specific for the global millisecond dynamics of the protein under study.


1.4 a simple model

Before further analyzing the data, it is important to summarize briefly

the results presented so far. I will also present the simple thermodynamic

model, which can be used to describe the observed effect.

From the results section presented before, three conclusions can be

derived:

1. The observed transition is reproducible if the cooling is sufficiently

fast

2. The transition can only be observed reliably if there is no glass-formingsubstance (such as glycerol or similar anti-freeze agents) present in thesystem.

3. The transition is specific for the protein, and also global for a given

protein molecule (i.e. it does not depend significantly on the nature,

and position of the chromophore probe used to monitor the tran-

sition). As a working hypotheses it can be assumed, that the oxy-

gen molecules present in the system are mainly responsible for the

quenching of phosphorescence, and they act as “test-molecules”:

If there is sufficient dynamical activation in the protein molecule,

then the diffusion becomes greatly enhanced, which leads to an in-

crease of the quenching efficiency, and a corresponding drop in the

average lifetime.

Several experimental and theoretical works deal with the so called “glass-

transition”, the thermal activation of proteins at cryogenic temperatures.

Several experimental techniques have been applied to study the phe-

nomenon, mostly optical absorption, neutron scattering and Mössbauer

spectroscopy[108, 97, 42, 41, 40, 39, 35, 34, 27, 28]. Recently NMR has

also been used to monitor the protons of water molecules[138, 137, 78].

I have already cited some of the most recent relevant articles, and it is

important to decide, if the observed dynamical transition is of the same

nature as described in these articles, or something different. There is a

specific feature of the glass-transition, which can be used for additional

comparison beyond the difference between the samples containing none

and 60% glycerol. The glass-transition as measured with these techniques

is usually a relatively broad transition on the temperature scale, as can be

seen, e.g., in Figure. 4 of [35], and is usually represented in an Arrhenius-

type of diagram. In Figure 11 an overlay is shown, with the quenching

rate constants (kq = 1/<t> - k0) of Zn-HbA (red) and the Zn-PP/DMSO

36 1.4 A simple model

Figure 11: Arrhenius plot of the Zn-HbA data (red) and Zn-PP/DMSO data(green) overlay-ed with Fig.4 from [35]. BA,DA and “exit” representvarious rate constants measured in Mb, while α and β represent thetwo types of fluctuations.

3 4 5 6 7 81000/T

log

(k)

(green). It can be seen that while the Zn-PP/DMSO data-set somewhat

resembles the glass-transition data of Figure 4. of [35], the Zn-HbA data

is strikingly different. It is important to note, that the timescales obvi-

ously play a major role in the observed effects, and with the experimental

method of phosphorescence quenching I am only monitoring a specific

time-window of a few hundreds of microseconds up to seconds. Other

techniques such as neutron-scattering and Mössbauer spectroscopy are

sensitive to processes of a totally different time-scale. This may also lead

to the very different nature of the observations. While it can not be totally

excluded that the transition of the protein is related to the glass-transition

phenomenon (since a similar transition temperature of approximately

210 K was observed in some cases in Mb and hemoglobin [81, 97]) ob-

served previously, the very different behavior on the temperature scale

may justify the effort of building a simple model which can account for

the observed effect.

First, I will present the simplest possible qualitative description, and

then a quantitative model will be presented.


1.4.1 Qualitative model of the thermal activation of millisecond protein dynam-ics.

Proton NMR studies in the ~500 ms time-window of motions in bovine

serum albumin (BSA) in a temperature range similar to the one investi-

gated in this study yielded data for the proportion of mobilized water

protons in the hydration layer around the protein, in water regions co-

ordinated to the buffer components and in icy structures of the buffer,

selectively[138, 137]. The cooling and warming protocol in these studies

was very similar to our method. No mobile water molecules were ob-

served below 220 K, the mobilization of the hydration layer around BSA

became activated above this temperature, detected as an abrupt increase

in the number of mobile protons. When the temperature was further in-

creased, mobilization of the structured water around the buffer compo-

nents was first observed as a separate phenomenon on the temperature

scale, and then upon warming further, the melting of the bulk icy ma-

trix followed. These data provide strong support for the idea that the

activation of large-scale protein dynamics seen in our experiments is cou-

pled to the activation of dynamics in its surrounding hydration layer. A

very simple qualitative model of the thermal activation of millisecond

range of motions in our protein samples is outlined in Figure 12. Oxygen

molecules are shown as red dots, their diffusion ability is represented

with double-ended arrows. The protein is shown as a simple pictogram,

the chromophores are shown as blue squares. As a simplification not all

of the two Zn-PP-s and six Trp-s are shown, but only four general “chro-

mophores”, to emphasize that the model is not dependent either on the

number, or on the position of the chromophores inside the protein under

study. The boundary of the protein is marked with a thick line, this also

represents the protein - coordinated water molecules of the hydration

shell. “State 1” in this model is the frozen state, in which molecular oxy-

gen 9 is approximately equally “immobile” (thus having a negligible dif-

fusion coefficient) in the bulk solvent, in the hydration layer of the protein

and inside the protein matrix. It can be hypothesized that during the first,

low-temperature step of phosphorescence quenching, motions within the

protein (and maybe also in its closely coupled boundary of the hydration

shell) become activated. This leads to a dynamic state of increased, but

still limited oxygen diffusion in the coupled system (“State 2”). When the

temperature is further elevated, oxygen diffusion becomes activated also

9 Or any other diffusable quencher, I will only represent oxygen later in the discussion,but it can be applied to any other quencher as well.


Figure 12: Qualitative model of the dynamic transition. Zn-HbA data are shownin red, the pictograms represent three different states as discussed in1.4.1.

120 140 160 180 200 220 240 260 280 3000

1

Temperature [K]

norm

alize

d av

erag

e life

time

Protein matrix

Zn-PP-IX

O2 molecules

1

3

2


in the bulk matrix, causing a further increase in the quenching efficiency

through an increase of diffusion-coefficient of the quencher, allowed by

the increased dynamics of the bulk solvent matrix, which results in a fi-

nal reduction of the phosphorescence lifetime below the detection limit

of our instrumentation (“State 3”). This latter activation of the matrix is

surely related to the glass-transition, while the activation of the hydration

shell may be influenced by both the protein, and the bulk solvent.

The second transition is very complex, involving a coupling of the hy-

dration shell to the bulk solvent, and also the glass-transition. It is also

not specific for the protein, as can be seen in the comparison of Mb and

Zn-HbA in Figure 10. It is more interesting to focus on the first transition,

which seems to be specific for the protein, and according to the proposed

simple model only involves the protein itself10. Therefore the presented

qualitative model will only focus on this first transition from “State 1” to

“State 2” in Figure 12.

1.4.2 Quantitative model of the first transition

The presented simple thermodynamic model ignores the details of molec-

ular mechanisms and assumes that “State 2” corresponds to activated col-

lective dynamics in the protein. It is considered as a single particle in the “protein” is theprotein molecule +the tightlycoordinated watermolecules

sample from a thermodynamic point of view. At a certain temperature

the individual particles fluctuate between energy states and the probabil-

ity to find a single particle in its mth micro-state with Em energy is Pm.

We suppose that Pm is proportional to the respective Boltzmann factor:

Pm ∼ e−

Em

kT (6)

10 Of course the hydration shell can not be neglected, and it may induce a coupling to thesolvent also during this first phase. However, as apparent from the data, this additionaleffect does not modify the transition significantly, and as a first approximation it’s in-fluence can be neglected. Therefore I will assume from now on, that the first transitionis specific, and confined to the protein molecule. However the term “protein” must beextended: water molecules being tightly coordinated to the surface of the molecule haveto be included to the “molecule”, since their dynamics is essentially “tied” to the dynam-ics of the relatively large protein to which they are coordinated. These additional watermolecules may significantly influence the transition in the case of very small proteins,but the systems included in this thesis are all relatively large, and thus this modificationcan be assumed to be very small relative to the effects arising from the protein moleculeitself.


We suppose that the particles are identical, independent, and in the frozen

state of the environment (during the first transition) they are distinguish-

able. This assumption is supported by the fact that during the rapid cool-

ing process each protein is “trapped” in an individual conformational

state. Thus on the basis of ergodicity, the distribution of energy, P(E), is

given as:

P(E) ∼ Ω(E) · e−

EkT = e

−E− TS

kT (7)

where W(E) is the number of micro-states which have E energy. Since

the entropy is given as S = k lnW, where k is the Boltzmann constant,

one may further develop the equation into the final form of Equation (7).

In equilibrium states this formula can give the respective equilibrium

values of the physical quantities. In the model we suppose two energy

states: “1”: frozen with a long average lifetime, t0 (= intrinsic lifetime),

“2”: (higher energy state) with activated quenching that leads to an av-

erage lifetime td, decreased by a factor of Kd where td = t0/Kd. If the

number of molecules in the two states “1” and “2” are N0 and Nd, re-

spectively, the average lifetime of the ensemble can be calculated in this

model as:

< τ >=

n∑

i=1Niτi

n∑

i=1Ni

=N0τ0 + Ndτd

N0 + Nd= n0τ0 + ndτd (8)

where n0 and nd are the relative number of particles without and with

activated dynamics, respectively. It is important to note, that Equation (8)

expresses the same average lifetime as Equation (4). For the comparison

of data obtained on different chromophores and proteins it was useful to

normalize the average lifetime data:

< τ >

τ0= n0 + nd

τd

τ0= n0 +

nd

Kd(9)


Since every measurement was carried out in thermal equilibrium11, we

may use Equation (7) to determine the expected value of the relative

number of particles (n) in a given state. Thus it follows:

nd

n0= e

−∆E + T∆S

RT (10)

Here DE and DS are the (molar) energy and entropy differences be-

tween the frozen and thermally activated states of the particle. Taking

into account that the number of particles is constant (n0 + nd = 1), and

substituting the expressions for n0 and nd into Equation (9), we obtain

< τ >

τ0

(T) =1 +

1

Kd· e−

∆E + T∆SRT

1 + e−

∆E + T∆SRT

(11)

which yields the temperature dependence of the relative average life-

time, which can be directly fitted to the average lifetime data obtained

from the measurements by Equation (4). The parameters of the fitted

curves derived from the derivative representation (transition midpoint

temperature (TMP) and maximum slope value (SlMP) are obtained as:

TMP =∆E∆S

SlMP =∆S

4RTMP

1

Kd− 1

(12)

In the figures the solid lines fitted to the data points correspond to Equa-

tion (11) in the case of the first step. The model clearly fits the exper-

imental data very well, and the fitting thus yields the thermodynamic

parameters of the function. The thermodynamic parameters concerning

the first step are shown in Table 3.

1.4.3 Analysis of the thermodynamic parameters

The magnitude of the energy difference in Table 3 is comparable to the

energy of a few hydrogen bonds. The entropy change is comparable to

the denaturation entropy of about 2 - 5 amino acid residues[69]. These

11 At least close enough to thermal equilibrium so, that non-equilibrium processes shouldnot influence the results significantly.


Table 3: Thermodynamic parameters of fitting to the first transition step:ΔE (en-ergy change), ΔS (entropy change), TMP (midpoint temperature), andKd ( = τ0/ τd ) , ± s.d.

sampleDE DS TMP Kd

[kJ/mol] J/mol·K [K]

Zn-HbA (Zn-PP) 113.4 ± 4.4 532 ± 22 213.1 ± 0.3 2.0 ± 0.1

Zn-HbA (Trp) 93.0 ± 13.8 435 ± 76 213.9 ± 5.6 4.0 ± 0.7

Mb (Trp) 36.2 ± 6.0 182 ± 37 198.7 ± 4.9 10.6 ± 1.7

literature support the effort of building up a view of the thermally acti-

vated quenching mechanism. Collisions with O2 molecules may involve

an average “hop-distance” (mean free path) of a length of a few (2 - 5)

residues. Thus, collisional quenching is made possible by a limited - and

likely anisotropic - diffusion process inside the protein similarly to ligand

diffusion in Mb (see e.g. [21, 25, 136]), by “hopping” through transiently

opening spaces, which are created transiently by the global dynamics of

the structure. The very simple two-state thermodynamic model fits the

experimental data and yields realistic parameters12.

There is significant difference in the thermal activation of quenching be-

tween Zn-HbA and Mb as seen in Figure 10, also manifested in the ther-

modynamic parameters. Apparently, the conditions in Mb significantly

increase the probability of activated quenching based both on the energy-

and entropy-difference values (they are smaller than in Zn-HbA). In addi-

tion, the significantly lower activation temperature (TMP) in Mb implies

that in this case the energy-difference is relatively less significant than

the entropy-difference between the activated and non-activated states as

can be seen from Equation (12). The increased Kd points to a greater

efficiency of quenching in Mb. It is difficult to establish a detailed molec-

ular basis that explains the difference in the activation of millisecond

dynamics between Mb and Zn-HbA. The experiment itself is only capa-

ble of monitoring quenching, but can not distinguish between different

quenching events. The thermodynamic model that yields the compared

12 That the model yields realistic parameters does not prove that is “true”, but it does indi-cate, that it might even be true as well. We have to remember the message of the citationfrom the Bible: “we see through a mirror” during all our lives, and this is especially truein science. Every result, law is considered as a “working hypothesis” as long nothingcontradicts it. Then, if a contradicting experimental result is found and confirmed, thehypothesis has to be re-thought. What I am presenting here is a working hypothesis,which is at least self-consistent, and also consistent with the experimental data.


parameters describes both cases as ensembles of independently fluctuat-

ing molecules, where each protein is treated as a “particle”, as described.

Thus monomeric Mb molecules are compared to tetrameric Zn-HbA. A

first look at the enormous number of data concerning the cooperative

behavior of hemoglobin subunits in oxygen binding would suggest that

they should evidently form a dynamically coupled unit. A closer look,

however, yields very little direct information on the details of this dy-

namic coupling, e.g. on how the presence of the interfaces between the

subunits would influence the overall dynamics, whether there is a size ef-

fect involved, etc. Reported results of molecular dynamics simulation are

based on techniques that address different questions[154]. Dissociation

studies suggest that the separation of the tetramer into dimers requires

less energy than dissociation into monomers[105], thus this contact seems

to be looser, which may also affect the strength of dimer-dimer dynamic

coupling. Although studies by the Ackers group on the cooperative be-

havior of HbA formed of asymmetrically mutated dimers lead to the

conclusion that the dimers behave “autonomously” in the cooperative

oxygen binding effect[1], one would expect more evidence for declaring

the dimers to be dynamically uncoupled units in HbA. If this were the

case, however, then the dynamic difference between Mb and HbA could

be related to the very interesting dynamic role of the hydration layer in

the case of Mb versus that of the subunit interface partially bordering

HbA dimers.

Nevertheless, it can be stated, that possibly relevant thermodynamic parameterscan be calculated from the experimental data with the help of the simple thermo-dynamic model presented in this section. The next interesting question is, if theseparameters correlate with biological function, if these activation - energy and -entropy values have biological significance. This question can be at least partlyanswered, if one compares the dynamical transition of Zn-HbA under conditionsreflecting various different states of its biological function.

2B I O L O G I C A L S I G N I F I C A N C E

2.1 allosteric effectors

Hemoglobin is a tetrameric protein, which plays a vital role in the trans-

port of oxygen. It consists of two dimers of and subunits that reversibly

bind and release oxygen[104]. A simple view is presented in Figure 13,

some important structural elements are highlighted in the figure. The

description of this cooperative phenomenon has been most frequently

derived from the (MWC) two-state allosteric model[89] that attributes co-

operativity to a rapid equilibrium between two conformations of distinct

oxygen affinity of the whole tetramer. These distinct states are the fully

unliganded T-state and the fully ligated R-state. Szabo and Karplus[131]

modified the two-state model incorporating the stereo-chemical mecha-

nism suggested by Perutz[101] for the T → R switch, and introduced

ligation-induced tertiary changes within the T-state. In this extended

model (MWC-SK), it was proposed that cooperativity still works through

a ligation-induced shift in the equilibrium of states T and R, but the

model attributed importance in the conformational switch to certain changes

at the inter- and intra-subunit interfaces. Upon ligation in the T-state, the

network of inter-subunit interactions become perturbed, some (e.g. salt

bridges) become broken up to release the characteristic strain of the T-

state. The mechanism involves a rotation of one dimer with respect to

the other[8], thus reaching the more relaxed R-state, as depicted in Fig-

ure 14 . It has been widely reported that some molecules, referred to as

heterotropic allosteric effectors - such as Cl- ions, inositol hexaphosphate

(IHP), Bezafibrate (BZF), or 2,3-diphospho-glycerate (DPG) - considerably

lower the oxygen affinity (and thus shift the oxygen binding curve to the

right, as shown in Figure 15) of the T-state upon binding to HbA but not

to the heme1[46, 75, 82, 102]. The binding of these effectors is very dif-

ferent, and there is still controversy in the literature how and where they

exactly bind, especially Cl- and BZF are not well understood, while it is

known that IHP and DPG bind primarily through electrostatic interac-

tions into the central cavity[5, 65, 106]. The modulation of the oxygen dis-

1 Hence the name allosteric effectors: they influence the function of the protein withoutdirectly binding to- or in the vicinity of the active site.

45

46 2.1 Allosteric effectors

Figure 13: Atomistic crystal structure of hemoglobin (T-state, bound to inosi-tol hexaphosphate). The individual subunits are each colored differ-ently for clarity, the Zn-PP substitution of the heme groups in the β-subunits is marked with green, two of the six Trp-s are marked withred, the inter-dimeric interface region is emphasized with a brownline.

Zn-PP substitution

interdimeric interface

Trp. β37

β1

β2

α1

α1


sociation curves by allosteric effectors is addressed in the extended MWC-

SK model by the assumption that allosteric effectors bind specifically to

the somewhat larger central cavity of the T-state and stabilize this confor-

mation. This shifts the R T equilibrium in favor of the T-state and con-

sequently lowers the overall affinity to oxygen[103, 102]. The well known

Bohr effect and results reported for Cl-, also influencing the oxygen affin-

ity of the T-state[52, 119], show that, in a broader sense, H+ and Cl- can

also be considered as being members of the family of allosteric effectors.

Extended studies on the effect of allosteric effectors, however, indicated

that they not only bind to the T-state but also to the R-state[48, 144]. The

modulation of the oxygen association constants (KT and KR) in both states

was shown to occur at a much broader scale than previously known (65-

fold change in KT and 2000-fold change in KR; see [142, 155] for details).

These data initiated the reformulation of the earlier models for the al-

losteric action of heterotropic effectors. The recently proposed “global

allostery model”[155] supposes that the effectors can bind to both the

T- and R-states and that effectors induce direct tertiary conformational

changes2. These tertiary effects then lead to the detected changes in oxy-

gen association[155, 142]. Until now, no structural data have been pub-

lished for the complex of R-state human HbA with allosteric effectors; the

only available structure is that of horse HbA complexed to CO[121]. Re-

cently, however, a docking and molecular dynamics simulation study[73]

proposed models for the structure of HbA bound with the allosteric

effectors DPG, IHP, and 2-4-(3,5-dichlorophenylcarbamoyl)- methyl-

phenoxy-2-methylpropionoc acid. These results supported the model al-

lowing for binding of effectors also in the R-state and proposed primary

binding sites in the central cavity of the R-state tetramer, and thus sup-

porting the global allostery model described above.

If the proposed global allostery model is “true”, then the - though maybe

subtle - tertiary conformational changes caused by the binding of al-

losteric effectors could also influence the global dynamics of the HbA

molecule. If so, then this modified dynamics may result in a different ac-

tivation energy (DE) and activation entropy (DS) values, which can then

be detected by the method presented in the previous section. We have

2 Earlier models, including among others the MWC-SK, and its further extensions, sup-posed a change of the interfaces between the subunits, which is a quaternary effect, butnot a change in the tertiary structures of the subunits themselves. This assumption issupported by the fact, that no significant structural changes can be seen in- and in thesurrounding of the heme groups upon the binding of allosteric effectors. (Although thechange upon the R T transition very large, but it is not the direct effect of the bindingof the effectors.)

48 2.2 Effectors and the transition

chosen four different effectors to test this hypothesis: Cl-, IHP, DPG and

BZF, based on the literature, and our previous work[117, 72], the magni-

tude of their effect approximately follows this order: Cl-< IHP ≈ DPG <

BZF.

In the next section I will present and discuss the data obtained with the

new optical method.

2.2 effectors and the transition

As discussed, if the binding of heterotropic allosteric effectors influences

the dynamical state of the hemoglobin tetramer, then this should appear

in the change of the activation of this dynamics as well. With the opti-

cal method presented in this thesis, however, a special type of dynamics

is monitored, namely only those motions, which have a characteristic

time-window of approximately 10-5 ... 1 seconds. If there are changes in

these motions due to the binding of these effectors, then the tempera-

ture dependence of the phosphorescence quenching may also be differ-

ent in each case, and different from the state without these effectors. The

main goal is not to provide details of the mechanism of action of these

allosteric effectors, since the method is not capable of providing spacial -

structural information. Rather, my goal is to provide a “test-case” of the

method with these data: if differences can be detected between various ef-

fectors, and between the effector-bound and the “stripped” (without any

allosteric effector bound) samples, it can further support the idea, thatthe term “stripped”is widely used in the

HbA literature toindicate the absence

of allosteric effectors,therefore I will use it

throughout thethesis in this sense

as well.

the activation- energy and entropy values provided by the new method

may indeed have meaningful biological relevance.

2.2.1 Activation of global dynamics in the presence of allosteric effectors.

The next few figures present the data obtained on samples

bound to different allosteric effectors: Cl- in Figure 16, IHP in Figure 17,

DPG in Figure 18 and BZF in Figure 19. The average lifetime data are

shown in Table 4 together with the concentrations in which the effectors

were used. These concentrations were selected to match those used in

previous studies (for eg. [155, 141, 142] and references there) in the litera-

ture. Cl- ions were added to the samples in the form of NaCl. The samples

were also checked with absorption spectroscopy, and spectra were com-

pared to the data available in the literature. No significant differences

above noise level were found in any samples.


Figure 14: Schematic representation of the rotation of the two dimers with re-spect to each other during the transition between the two states of Rand T.

T R

deoxyhemoglobin oxyhemoglobin

Table 4: Average phosphorescence lifetime of Zn-HbA bound to allosteric effec-tors. For comparison the data of stripped Zn-HbA is also shown in thistable.

sample <t> at 10K [ms] ± s.d.

Zn-HbA stripped 28.7 ± 0.6

Zn-HbA + 100 mM Cl-28.9 ± 0.8

Zn-HbA + 2 mM IHP 29.0 ± 0.8

Zn-HbA + 2 mM DPG 27.6 ± 1.1

Zn-HbA + 10 mM BZF 28.0 ± 0.9


Figure 15: Oxygen binding curve of hemoglobin. The curve shows the oxygensaturation curve of the whole tetrameric molecule, thus 100% satu-ration is equivalent to the total binding of 4 oxygen molecules. Theshifting of the curve to the right (decreased binding affinity) is causedby allosteric effectors, and is shown with an arrow. In the bottom ofthe figure the structure of three different allosteric effectors are alsoshown.

Bezafibrate

(BZF)Diphosopho glicerate

(DPG)Inositol hexaphosphate

(IHP)

4 x O2

R : oxy

T : deoxy

Oxygen partial pressure [mmHg]

Perc

ent s

atur

atio

n (%

)


Figure 16: Normalized average lifetime of Zn-HbA bound to Cl-(purple curveand diamonds). For comparison stripped Zn-HbA is also shown withred. The negative derivative functions are also shown in the bottomgraph.

0

1

norm

alize

d av

erag

e life

time

160 180 200 220 240 260 280

temperature [K]

−Δ ⟨τ ⟩ΔT

It can be seen, that the binding of allosteric effectors modifies the curves,

and significantly change the first transition. The magnitude of the change

follows the order of Cl-< IHP ≈ DPG < BZF. While the binding of Cl-, IHP

and DPG cause a relatively small shift of the transition on the tempera-

ture scale, BZF causes a large shift accompanied by an also significant

broadening of the transition. The change of the second transition is not

as clear. While the differences of the transition points on the temperature

scale in the derivative representation may seem significant, the cases of

DPG and IHP have to be treated with caution: as can be seen, during the

first transition the drop of the lifetime is very large. As apparent from

Equation (5) the drop in the lifetime is accompanied by the same drop

in the intensity. This intensity reduction after the first transition - as can

also be seen in Table 5 comparing the Kd data - causes the signal/noise

ratio to also significantly decrease, which makes the lifetime determina-

tion less certain (the relative error is much higher in these cases than

average, reaching up to 15 ... 20 %). The increased error then causes an

uncertainty in the fitting of the sigmoid function to the second transi-

tion, which manifests itself as an uncertainty in the second “peak” of the

derivative functions.


Figure 17: Normalized average lifetime of Zn-HbA bound to IHP (blue curveand triangles). For comparison stripped Zn-HbA is also shown withred. The negative derivative functions are also shown in the bottomgraph.

160 180 200 220 240 260 280

temperature [K]

−Δ ⟨τ ⟩ΔT

0

1no

rmali

zed

aver

age

lifetim

e

2.2.2 Analysis of the differences caused by allosteric effectors

The thermodynamic parameters calculated from the fitting of Equation (11)

to the data are shown in Table 5. Changes in the second transition may

not be relevant due to the factors described before, however, they can also

arise from the perturbation of the hydration shell caused by the millimo-

lar concentration of “foreign” molecules compared to the stripped case.

While the time-scales and the systems are very different, the importance

of the environment is emphasized in the literature of glass-transition in

proteins (see for eg. [96]). In the analysis of the dynamical transition (1.4)

it was shown that the second step includes the coupling of the protein to

the bulk solvent as a major effect. This can not be excluded from the anal-

ysis of the differences caused by allosteric effectors. Most notably, this

effect is evident in the case of Cl-, which sample involved the addition

of 100mM NaCl to the 100mM HEPES buffer. This effectively doubles

the molarity of the solvent, and acts as an anti-freeze agent3. This can

3 Addition of salt is widely used to avoid freezing of water, or at least considerably lowerthe freezing-point. A corresponding decrease of the melting-point is also evident in thiscase.


Figure 18: Normalized average lifetime of Zn-HbA bound to DPG (orange curveand triangles). For comparison stripped Zn-HbA is also shown withred. The negative derivative functions are also shown in the bottomgraph.

0

1

norm

alize

d av

erag

e life

time

160 180 200 220 240 260 280temperature [K]

−Δ ⟨τ ⟩ΔT

Table 5: Thermodynamic parameters of the first transition in different Zn-HbAsamples. For comparison the data from Table 3 of the stripped from(and calculated from Zn-PP lifetimes) are also shown ± s.d.

sampleDE DS TMP Kd

[kJ/mol] J/mol·K [K]

Zn-HbA stripped 113.4 ± 4.4 532 ± 22 213.1 ± 0.3 2.0 ± 0.1

Zn-HbA +100mM Cl-97.7 ± 5.6 456 ± 29 214.2 ± 0.7 5.33 ± 0.43

Zn-HbA + 2 mM DPG 71.5 ± 3.7 327 ± 27 218.5 ± 0.6 29.38 ± 3.03

Zn-HbA + 2mM IHP 77.4 ± 3.5 358 ± 24 216.4 ± 0.4 31.46 ± 2.85

Zn-HbA + 10mM BZF 42.3 ± 1.7 187 ± 10 225.9 ± 2.5 17.85 ± 1.96


Figure 19: Normalized average lifetime of Zn-HbA bound to BZF (dark greycurve and triangles). For comparison stripped Zn-HbA is also shownwith red. The negative derivative functions are also shown in the bot-tom graph.

0

1

norm

alize

d av

erag

e life

time

−Δ ⟨τ ⟩ΔT

160 180 200 220 240 260 280temperature [K]

account for the observed shift of the second transition by almost -10 K,

since due to the decreased melting point the state “3” on Figure 12 will

be reached at a lower temperature.

The first transition was shown to be specific for the protein, therefore

it is of greater importance in the search for biological significance of

the results available from the new method. In Figure 20 the curves are

shown in a common figure to aid comparison of the first transitions. To

emphasize the fact that the second transition is of less importance, it is

shown in pale colors. The activation energies and entropies also change

significantly upon the addition of allosteric effectors. Both the activation

energy- and entropy- values are significantly smaller than in the stripped

case, Cl- ions having a relatively moderate effect, while DPG and IHP

decrease these values by about 30%, and BZF by more than 50%. The

magnitude of the change in the DE and DS values corresponds to the ef-

fector strength: Cl- < DPG ≈ IHP < BZF. This shows that the special type

of dynamics monitored by the quenching experiment can be more eas-

ily activated in the hemoglobin+effector complexes. This may indicate a

“softening” of the structure caused by the effectors, which may correlate

with the decreased dissociation volume of the tetrameric structure found


Figure 20: Comparison of the first transition of Zn-HbA under various condi-tions: stripped (red), with added Cl-(purple), with added DPG (or-ange) and added BZF (dark grey). The respective derivative functionsare also shown in the bottom. To emphasize the importance of the firsttransition, the second half of the curves are shown in pale colors.

0

1

norm

alize

d av

erag

e life

time

160 180 200 220 240 260 280temperature [K]

−Δ ⟨τ ⟩ΔT

in our pressure tuning experiments[117, 72].

The change in the Kd values indicate also that there is a change in the

diffusion coefficients of the quenchers inside the protein, and addition

of the allosteric effectors generally increases the diffusion rate. This also

indicates some kind of “softening”, however regarding the molecular de-

tails no solid inference can be drawn from these data. It can also be seen,

that the relative drop in the activation entropy values is larger than the

relative drop in the activation energy values, thus the activation of the

dynamics becomes proportionally more “energy-intensive”, and the ra-

tio of the released entropy is smaller. This accounts for the increase in the

transition temperature (TMP).

Of course, taking into account other experimental data (pressure tun-

ing and fluorescence line narrowing, as will be shown in the next sec-

tions), possibly interesting speculations can be made, and I will attempt

to present some of them in chapter 5. In short, most probably the path-

ways of the quenchers are changed by the addition of allosteric effectors,

due to a realignment of the dynamic fluctuation patterns of the struc-

ture. This realignment then may play a role in transmitting information

through the interfaces between the monomeric subunits, and may also


serve as an information “pathway” through the entire structure. This

way allosteric effectors may influence the function of hemoglobin (and

possibly other allosteric proteins may function in a similar way) not only

through static structural changes, but also through influence on the dy-

namic global movement patterns of the entire structure of the protein.

These are of course speculations only, the data do not allow for more

than to observe the changes in the activation parameters of the ms ... s -

timescale global dynamics.

It can however, be stated, that the new optical method presented in this thesissupplies activation - energy and - entropy data of a special kind of global, slowdynamics of the protein which correlates with it’s biological function in a sense,that any biologically significant changes in the protein’s function also manifestsin changes of these activation parameters.

This dynamics is not identical to the dynamics of the same time-scales

at room temperature, since the boundary of the protein is bound to a

solid matrix during the first transition. However, this limited dynamics is

still representative for the protein, and reflects in some way it’s dynamics

under physiological conditions. The exact differences between this lim-The resultspresented in the next

sections are betterunderstood in a

retrospective way,therefore they are

presented in thelight of the results of

the new method.

ited dynamics and the dynamics under physiological conditions can not

be inferred to with this technique unfortunately4.

In the next sections I will present results of other experiments (pressure-

perturbation, and fluorescence line narrowing) done on hemoglobin pre-

viously during my PhD-work. These data can be put in an interesting con-

text knowing that there is a change in the global dynamics of hemoglobin

by the addition of allosteric effectors, than without this result.

4 Maybe NMR, or other site-selective method will be able to add data to these questions,however the time-scale of ms ... s is still hardly accessible.

3C H A N G E S AT T H E I N T E R FA C E S - P R E S S U R E

P E RT U R B AT I O N

3.1 introduction to pressure perturbation studies

In this section results of a pressure-perturbation study are presented.

These results can be related to the results presented in the previous sec-

tion. High pressure is known to have distinct effects on proteins [58] de-

pending on the applied pressure range. Typically, 0.5 ... 1 GPa is needed

to denature a protein, by squeezing water into the interior [125]. Lower

pressure causes elastic deformations, the extent of which are characteris-

tic of the compressibility [71, 36] of the protein. Because pressure is an

intrinsic thermodynamic parameter, pressure can shift thermodynamic

equilibria of various kinds, including conformational transitions of pro-

teins [9]. One such equilibrium that is typically perturbed by pressure is

oligomer dissociation. Pressures in the range of 100 ... 200 MPa have been

shown to be able to affect the quaternary structure of the proteins without

affecting their secondary and tertiary structure [124, 123]. Previous pres- Due tospace-restrictionsthis is only a veryshort introduction topressure-tuning,interested readersare directed to thecited references fordetails about thetheory andmethodology.

sure experiments performed on HbA [105, 90, 2] showed that pressure

tuning affects various optical properties (e.g. light scattering, absorption,

fluorescence emission, and CD-spectra) of the sample. In a detailed study

[105] it was shown that applying pressure at pH 7 and 10-6... 10

-4 M pro-

tein concentration will shift the tetramer dimer equilibrium in favor

of the dimers, and at pH 9, the observed dimer monomer equilibrium

will be shifted in favor of the monomers. No systematic study applying

pressure perturbation was conducted to observe the effect of various al-

losteric effectors on the subunit interfaces in HbA. It was our goal to

compare the effect of allosteric effectors on the tetramer dimer equi-

librium in the T- and R-states by applying high hydrostatic pressure and

steady-state fluorescence techniques. Based on literature data [64, 112],

we have used the intrinsic fluorescence of the tryptophan residues as a

marker of changes at the interface region. Measurements under high hy-

drostatic pressure were, however, not feasible on deoxyhemoglobin, be-

cause the sample holder inside the pressure cell cannot be isolated in a

gas-tight manner from the pressure transmitter fluid (water) in the de-

vice. To overcome this difficulty (and for its multiple chromophores), we

57

58 3.2 Method of pressure perturbation

used Zn-HbA to mimic the structure of the T-state. Oxygen equilibrium

studies and x-ray crystallography have shown that this derivative, as a

five-coordinated metal hybrid of HbA, can be considered analogous to

T-state HbA, although not being perfectly the same [98, 120, 18]. The use

of zinc substitution is supported by results that show a low energetic

cost compared with other (for e.g. cobalt) metal substitutions [64]. This

indicates that the conformation is relatively close to the native form. It

can be considered questionable, however, for which of the T-state sub-

populations the analogy holds. The conformation within being “T” was

shown to be slightly tunable by environmental conditions, for example

by sol-gel encapsulation [112, 113]. This tunability was also found within

zinc hybrids rendering the CO-ligated form the least tense among a vari-

ety of ligated forms and external conditions [111]. Literature data, how-

ever, show that the zinc hybrids in general have lower oxygen affinity

than deoxy-HbA [87]. Based on this we considered Zn-HbA form, which

may be the least tense among the zinc hybrids, a sufficiently good model

for the native T-state. Oxygen saturated, non-hybrid HbA was used to

study the R-state, it is termed “oxy-HbA ” in this thesis.

3.2 method of pressure perturbation

3.2.1 Fluorescence Emission Spectra under High Pressure

A high pressure cell with sapphire windows was mounted in a spectroflu-

orometer , as seen in Figure 21. The figure shows the current setup, in

which a custom-modified spectrometer is used. Data presented in this

section was acquired with the use of a previous setup, in which the high-

pressure cell was mounted in a Fluorolog-3 spectrometer. That setup had

a lower efficiency, since the optics of the spectrometer did not match

the numerical aperture of the cell. To improve the signal-level, I have re-

designed the system, and built it around a Hitachi spectrometer, which

was modified to adapt it to the optics and geometry of the pressure cell.

The optical path is also shown in the figure (excitation path in light blue,

emission path in light green), together with the added optical elements.

Two Ø 6.3 mm focusing lenses are fit into the window-plugs of the cell,

to focus / parallelize the beam, other lenses are used to obtain a matched

numerical aperture to the monochromators. High pressure was created

by a manually driven piston pump (Nova Swiss, Effretikon, Switzerland),

and pressure was monitored with a pressure transducer (DMS-580.4018


Figure 21: The current high pressure setup. Drawing of the high-pressure cell,image of the modified spectrometer, and of the whole setup. Lightpaths are shown in blue / light green for excitation / emission re-spectively, the used quartz cuvette is also shown with its stopper.

sapphire window

window cap

teflon ring

torlon ring

brass ring

window plug

high-pressure plug

spacer

excitation lens1

excitation lens2

emission lens

focusing lensesin the cell's window plug

high pressure cell piston pumpflush/release valve

pressure transmitter

60 3.2 Method of pressure perturbation

Nova Swiss, Effretikon, Switzerland) equipped with a digital meter, with

an accuracy of 10 bar. The sample was allowed to equilibrate at each pres-

sure for 3 minutes. Repeated spectra at the same hydrostatic pressure

did not show detectable differences after this time, therefore it could

be concluded that equilibrium was reached. Spectra were acquired by

counting the detected photons for 1s at each wavelength, with slits of the

monochromators adjusted at 5 nm excitation and 2 nm emission band-

pass. The temperature was maintained by a thermostat at 20 °C and was

directly controlled in the sample with a special thermometer rated for

7000 bar maximum pressure. The HbA sample was injected into a quartz

tube (UV-fused silica) with a 2.4-mm inner diameter with 1.3-mm wall

thickness and 19-mm height. The sample volume was 110 µl. This tube

was covered with a rubber stopper and placed into the pressure cell. The

pressure transmitter fluid was water. Spectral shift under pressurization

was determined based on either the maximum position of the emission

band determined by a Savitzky-Golay algorithm[114].

It was important to control the state of the protein under high pressure. We

wanted to avoid any secondary or significant tertiary structural changes

during the experiments. Therefore it was important to determine the

“safe” pressure range. Two methods are especially suited for these con-

trols: UV-VIS absorption spectroscopy - as already mentioned - is highly

sensitive to tertiary structural changes to the environment of the chro-

mophores, and FTIR spectroscopy, which is a useful tool to estimate sec-

ondary structural elements.

3.2.2 Absorption Spectra at High Pressure

The high pressure cell was mounted in a Cary 4E UV-visible spectropho-

tometer (Varian Inc, Palo Alto, CA) and kept at 20 °C. Spectra were ac-

quired at a scan rate of 1 nm/s, using the full height slit mode, allowing

for 1 nm bandpass. Control spectra before pressurization were acquired

in the quartz tube, covered with a rubber stopper, and placed centered in

the light beam.

3.2.3 FTIR Spectroscopy Under Pressure

The infrared spectra - to control possible changes in the secondary struc-

ture of the protein caused by high pressure - were obtained with a Bruker

IFS66 FTIR spectrometer equipped with a broad band MCT solid-state de-


tector cooled with liquid nitrogen. During data acquisition, 256 interfero-

grams were summed at a resolution of 2 cm-1. High pressure was gener-

ated in a diamond anvil cell (Diacell Products, Leicester, UK), where the

pressure was built up by means of a screw mechanism, which pressed the

two diamonds against each other. The sample was held in the boring of

a steel plate (gasket) between the diamonds. Sample volume was approx-

imately 50 nl. Barium sulfate was used as an internal pressure standard

in all cases[153]. All experiments were performed at 20 °C, and at a pro-

tein concentration of 800 µM. The broad band of water around 3350 cm-1

was used to control that the solvent is still in the fluid phase even at

the highest pressure used in the experiments. No crystallization was ob-

served in the experiments reported here. The overlapping components

of the amide I/I band were resolved by Fourier self-deconvolution[70],

which decreases the width of the component lines of the amide band.

The optimal parameters were determined from the analysis of the power

spectrum[127]. A resolution enhancement factor[70] of 1.5 was reached by

using a Lorentzian band shape of 20 cm-1 bandwidth. The deconvoluted

spectra were then fitted with gaussian functions, and the peak position

of the band characteristic for a-helical structure was determined.

3.3 pressure perturbation results

Oxy-Hb and Zn-HbA samples corresponding to the R- and T-analogue

state HbA, respectively, were studied in stripped condition as reference

and then bound to various allosteric effectors. The effect of allosteric

effectors was monitored by registering the conformational perturbation

effect of high pressure using fluorescence emission and absorption spec-

troscopy. For the interpretation of the results it was important to compare

the results of HbA to a similar, but monomeric protein, Mb. I will only show dataof Zn-HbA in thestripped condition,the spectra and theirshifts were similaralso in the cases ofadded allostericeffectors.

3.3.1 Control experiments

It was important to exclude the possibility of denaturation or any signif-

icant tertiary structural changes during the pressure perturbation exper-

iment. As mentioned before, absorption spectroscopy is a useful tool to

monitor any of these events. The results obtained by FTIR spectroscopy

are shown in Figure 22, the spectra are shifted along the absorbance-axis

for clarity. The blue lines show the FTIR spectrum of HbA at ambient

pressure, the light-blue line is the deconvoluted spectrum, and dashed

62 3.3 Pressure perturbation results

Figure 22: FTIR spectra of HbA and Mb at ambient pressure (blue lines), at 325

MPa (red line) and at 900 MPa (black line). The position of the posi-tion of the amide-I peak of α-helical content at various pressures arealso shown for HbA (squares) and Mb (triangles) together with theirs.d.

1580 1600 1620 1640 1660 1680 1700 1720wavenumber [1/cm]

abso

rban

ce [a

.u.]

Gauss decomposition

p = atm

p = 325 MPa

p = 900 MPa

0 100 200 300 400 500 600 700 800 9001630

1635

1640

1645

1650

1655

p [MPa]

α-he

lix p

ositio

n [1

/cm

]


Figure 23: Absorption spectra of HbA at ambient pressure (blue line) and at 350

MPa (red line). Inset shows the absorption maximum of the Soret-band around 409 nm at various pressure levels.

350 400 450 500 550 600 650wavelength [nm]

abso

rban

ce [a

. u.]

0 50 100 150 200 250 300 350 400408

409

410

411

pressure [MPa]

Max

. pos

. of S

oret

ban

da [n

m]

lines show the Gaussian-fitting, to obtain the peak position correspond-

ing to the a-helices in the protein. It can be seen that the FTIR-spectrum

corresponding to 3.25 kbar (325MPa) does not differ significantly from

the spectrum at ambient pressure, thus up to this hydrostatic pressure

no significant secondary-structural changes can be seen. The position of

the amide-I band corresponding to the a-helical content of the protein is

also shown at various pressure values for HbA (squares) and Mb (trian-

gles). It can be seen, that there is a very slight shift of the amide band

at the beginning, which can be attributed to elastic compression of the

entire structure, and then above 4 kbar the slope increases, and a phase

transition follows. To avoid any onset of a phase transition, we have cho-

sen 3.5 kbar as the upper limit of the applied hydrostatic pressure for any

subsequent experiments.

To further test against any tertiary structural changes, we have obtained

UV-VIS absorption, and fluorescence emission spectra. The absorption

spectrum of HbA at ambient pressure (blue line) and at 3.5 kbar (red

line) are shown in Figure 23, the inset shows the absorption maximum

of the Soret-band around 409 nm at various pressures. A slight, linear

shift can be seen, which corresponds to shifts usually seen in the case of

elastic compression of the structure. Similar shift was observed, e.g., in


Figure 24: Fluorescence emission spectra of Zn-HbA at ambient pressure (blueline) and at 350 MPa (red line). Inset in the figure shows the peakposition of the Q-band of Zn-PP at various pressure levels. Excitationwas at 290 nm wavelength.

300 350 400 450 500 550 600 650 700wavelength [nm]

fluor

esce

nce

int.

(a.u

.)

0 100 200 300 400593

594

595

596

597

pressure [MPa]

Zn-P

P em

. pos

. [n

m]

the case of cytochromes under pressure[67]. The Zn-HbA sample having

two different chromophores at different places in the structure enabled

us to further test the effect of hydrostatic pressure in this range.

The fluorescence emission of Zn-HbA is shown in Figure 24. It can be

seen, that the changes in the Trp emission region (around 340nm) are

significantly different from the change at the Q-band region of the Zn-PP

emission (around 595nm). The spectrum was acquired with an excitation

wavelength of 290 ± 2.5 nm (thus 290 nm with 5nm bandpass). The Trp

fluorescence is seen around 340 nm, while the fluorescence emission of

Zn-PP is also visible due to Förster-type energy-transfer from the Trp-s to

the Zn-PP-s[49] (and to the two other heme groups as well). It can also be

seen as a slight “dip” around 408 nm in the Trp emission spectrum. This

could be further confirmed by registering the excitation spectrum of Zn-

HbA at an emission wavelength of 595 nm, it had both the characteristic

excitation spectrum of Zn-PP, and an additional peak at 290nm corre-

sponding to the excitation maximum of Trp as can be seen in Figure 25.


Figure 25: Excitation spectrum of Zn-PP in Zn-HbA.

270 320 370 420 470 520 570excitation wavelength [nm]

fluo.

int

. at 5

94nm

3.3.2 Transitions seen in the Trp fluorescence

The Trp fluorescence emission is distinct from the behavior of the Zn-PP.

It also shows a shift of the emission maximum position, and it is accom-

panied by a large intensity increase, as can be seen in Figure 24, and in

the case of non-hybrid oxy-HbA shown in Figure 26. . These changes are

not linear however, as can be seen in Figure 27. This non-linearity is in

sharp contrast to the perfectly linear behavior of Zn-PP in Zn-HbA, or

the Trp in Mb, and shows a transition, which is not present in other data.

It is also a striking difference, that the Trp emission intensity decreases in

Mb together with the linear red-shift of the spectrum, while in HbA there

is an intensity increase both in Zn-HbA and oxy-HbA. Before reaching any

further conclusions, and discussing the results, it is important to rule out

possible denaturation of the structure, as a cause for this different behav-

ior. Most of the control experiments target this goal, I will summarize This could be part ofthe discussion, but itmay be better tohave it here, thereare other points todiscuss later.

here the rationale for excluding denaturation.

3.3.3 Transition seen in HbA is not caused by denaturation

3.3.3.1 The 100 ... 200 MPa pressure range is very low.

compared with the typical pressures needed for protein unfolding. It

was shown previously that myoglobin is pressure-stable up to 650 MPa

[58, 128, 83]. Data presented for Mb also show no signs of any significant

structural change. Recently a denaturation pressure of 400 MPa was re-

ported for the isolated subunits of HbA[53], but the observed 100 ... 200


Figure 26: Trp fluorescence emission of oxy-HbA at ambient pressure (blue line)and 3.5 kbar (red line). The inset shows the normalized emission spec-tra to emphasis the spectral shift accompanying the intensity increase.

300 320 340 360 380 400 420 440 460 480 500

wavelength [nm]

fluor

esce

nce

int.[

a.u.

]

280 300 320 340 360 380 400 4200

1

wavelength [nm]

nom

alize

d flu

ores

cenc

e

MPa transition pressure range - as seen in Table 6 - is significantly lower,

and thus it is not reasonable to expect denaturation at this lower level of

pressure.

3.3.3.2 Absorption spectrum at 350 MPa.

At this pressure the Trp emission is already red-shifted with respect to

the initial emission spectrum. No significant changes, except a slight red

shift, can be seen in the Q-band and in the Soret region. Denaturation of

the protein would be clearly seen in the absorption spectrum, as can be

seen, e.g., in the slow-cooled sample Figure 4. Also, as observed in the

Q-band region, no change in the spin state or in the coordination state

of the heme occurs in the pressure range used. The small linear shift of

the Soret-peak in the absorbance spectrum in Figure 23, and the Q-band

emission-peak (around 595 nm) of Zn-PP in Figure 24 can be explained

by the change of the electronic transition energy due to applying high

pressure that decreases the distance between the chromophore and the

interacting units (atomic groups). This change of the electronic transition

energy is supposed to be proportional to the solvent shift at atmospheric

pressure. If the interaction of the chromophore with the atomic groups

of the protein matrix is dominated by one kind of interaction with a po-

tential energy of 1/Rn distance dependence, one observes a linear shift


Figure 27: Fluorescence emission of Zn-HbA at various pressure levels. The topfigure shows the maximum position of the emission, the bottom fig-ure shows the emission intensity at the maximum. Insets in both fig-ures show the respective data for Mb.

0 50 100 150 200 250 300 350 400331

332

333

334

335

336

pressure [MPa]

Trp.

em

issio

n m

axim

um [n

m]

0 100 200 300327

328

329

330

331

332

333

pressure [MPa]

Mb

em. m

ax. [

nm]

0 50 100 150 200 250 300 350

pressure [MPa]

Trp

fluor

esce

nce

int.

[a.u

.]

0 50 100 150 200 250 300 350pressure [MPa]

Mb

fluo.

int.

[a.u

.]


of the transition energy as a function of pressure [74, 158, 157]. The ob-

served linear red shift has also been reported for other heme proteins

[128, 67], and shows that the structure of the heme pocket in general was

not affected, and we only see an overall elastic effect.

3.3.3.3 This pressure range typically affects intermolecular interactions.

It is well known that pressures of this range typically affect intermolec-

ular interactions and cause the dissociation of oligomers[124, 123]. An

earlier HbA fluorescence study [105] found reduced molecular volumes

calculated from the fluorescence lifetime and anisotropy of a covalently

attached fluorescent label 5-dimethylaminonaphthalene-1-sulfonyl chlo-

ride (dansyl chloride) under pressures up to 250 MPa. The authors inter-

preted these changes in terms of dissociation and not denaturation.

3.3.3.4 Changes are not due to altered oxygen binding.

Besides conformational changes induced by pressure, we have to con-

sider the possibility of deoxygenation because of pressure. This, however,

would lead to almost a magnitude stronger shift of the Soret band (an

almost 20nm red-shift of the Soret band would occur upon deoxygena-

tion) than the shift observed. Thus, we can rule out pressure-induced

deoxygenation in this pressure range.

3.3.3.5 FTIR spectroscopy.

FTIR spectra do not show significant changes in the amide-I band posi-

tion (characteristic for a-helical structure) up to 350 MPa, as can be seen

in Figure 22. Because HbA is a predominantly a-helical structure, this

rules out unfolding of any helices in this pressure range. To demonstrate

pressure - induced unfolding, the FTIR spectrum acquired at 900 MPa

is also shown which clearly shows an unfolded state. This spectrum is,

however, very different from the ones corresponding to the lower pres-

sure range.

3.3.3.6 Comparison with Mb.

Mb is a monomeric heme protein, and its tertiary structure closely re-

sembles the structure of a HbA subunit, therefore it can be considered

as a good model of a single HbA monomer. In the same pressure-range

Mb behaves strikingly different however than HbA: both the shift of the

maximum position and the intensity change are strictly linear. It has been

reported in the literature how pressure itself influences the fluorescence


spectrum of Trp in tris(hydroxymethyl)aminomethane buffer, in the pres-

ence of alcohol or glycerol, and when it was incorporated in a small

peptide[110]. In all cases a linear, continuous red shift induced by pres-

sure was observed. This effect - attributed to the increase of water density

and dielectric constant under pressure - would cause a shift of 1 ... 2 nm

in the pressure range used here. The shift of the maximum position in

our measurements is in this range, although somewhat larger, which can

be attributed to the presence of the protein matrix. It is interesting to

note that this red shift is comparable with the shift of the fluorescence

maximum position of Zn-PP, showing the presence of the same elastic

compression in HbA. None of the transition-like features of HbA appear

in the fluorescence of myoglobin. It should also be considered that an

elastic compression, which shortens the heme-Trp distance, would itself

decrease the intensity of the Trp fluorescence because of an increase in

energy transfer. This latter effect is expected to occur also in HbA but

is overwhelmed by another effect, which can be attributed to pressure-

induced dissociation of the tetramer.

3.4 discussion of the pressure perturbation results

The observed transition in the Trp fluorescence data of HbA, as seen

in Figure 27 is of sigmoidal shape. The point corresponding to the half-

transition, p½ is distinct under different conditions, such as protein con-

centration, or the presence of allosteric effectors, both in the case of oxy-

HbA, and Zn-HbA. The p½data are shown in Table 6, the s.d. of the p½

values is 3 ... 5 MPa. The p½data are all in the 100 ... 200 MPa range, and

the presence of allosteric effectors significantly modify these values. In

the case of Zn-HbA the transition pressure decreases, while in oxy-HbA

it increases.

3.4.1 The transition is related to dissociation.

As already mentioned, this transition can be interpreted as a pressure-

induced dissociation of the tetrameric structure into two monomers. This

interpretation is supported by the following rationale:

3.4.1.1 Trp-s in the interface region.

The HbA tetramer has six Trp residues, one in each a- and two in each

b-subunits. It was realized a long time ago that Trp fluorescence could

70 3.4 Discussion of the pressure perturbation results

Table 6: Mid-transition pressure values (p½) of oxy-HbA and Zn-HbA under dif-ferent conditions.

Hb typeconcentration added effector p½

[mM] (with conc.) [MPa]

Zn-HbA

0.68

none (stripped)

200

0.23 160

0.02 135

0.06 140

0.06 100 mM Cl-113

0.06 2 mM DPG 94

0.06 2 mM IHP 72

0.06 10 mM BZF 165

oxy-Hb

7.7

none (stripped)

225

0.77 157

0.06 100

0.06 100 mM Cl-137

0.06 2 mM IHP 144

0.06 10 mM BZF 170


be used to monitor conformational changes i.e. T R transition, and

this sensitivity of the signal was assigned mostly to Trps b37 which are

located at the a1b2 and a2b1 subunit interfaces[61, 62, 60]. In resonance

Raman spectra obtained by UV excitation the contribution assigned to

these Trp residues can be separately analyzed and used to monitor lo-

cal structural changes in the interface region [112, 113]. In a fluorescence

study, the sensitivity of the signal to structural changes relies significantly

on the conditions for quenching by Förster-type energy transfer to the

hemes. The Trps in HbA are within short distances from one or more

hemes of the structure, thus the distance requirements of energy trans-

fer are fulfilled (data can be seen in [117, 72]). This also explains that

the fluorescence of Zn-PP can be excited through Trp excitation at 290

nm as seen in Figure 24. The energy transfer is also indirectly detectable

through the relatively low quantum-yield of the Trp fluorescence. Energy

transfer could also be tracked down indirectly by the low quantum yield

of Trp emission in HbA. The b37 Trp is the Trp closest to the neighboring

a subunit heme (Trp b137 to the a2 heme, and Trp b237 to the a1 heme).

This distance is liable to become easily perturbed by changes at the inter-

dimeric interface. It should be noted however, that Trp a114 , Trp b115

and Trp b137 are within a short distance of their respective intra subunit

heme group (the same holds for Trp a214 , Trp b215 and Trp b237), thus

are also subject to energy transfer to their heme groups, but since this

heme is part of their respective subunits, a possible dimer-dimer separa-

tion should not perturb this type of energy transfer significantly. Further-

more, Trps a14 and b15 are far away from the interface, a change at the

interface region should not perturb their fluorescence properties signifi-

cantly. Based on the distance data, one can suppose that the fluorescence

of Trps b37 will be sensitive to dimerization.

3.4.1.2 Red shift of the Trp emission.

Red shift is usually assigned to a local environment of increasing polar-

ity, as in the case of exposure to water[107, 149], however, changes in

the electric field and in the dipole moments around the Trp residue can

also result in the shift of the Trp emission spectrum[107]. Since pressure-

induced unfolding is ruled out, significant electric field or dipole mo-

ment changes in Trp surroundings can only be due to exposure to water.

The Trps b37 are somewhat buried in the tetramer, but become solvent

exposed in the dimer form. Thus a tetramer-dimer transition and a con-

sequent water exposure could explain the observed red shift.


Figure 28: Concentration - dependence of the p½data in oxy-Hb (squares) andZn-HbA (diamonds).

0.01 0.1 1 10100

125

150

175

200

225

250

concentration [mM]

trans

ition

pres

sure

[M

Pa]

3.4.1.3 Intensity increase during the transition.

Besides the red shift, the intensity of the fluorescence emission is increas-ing during the pressurization. This can be attributed to - and is consis-

tent with a decrease in the efficiency of the energy transfer to the heme

groups of the neighboring dimer due to the tetramer dissociation. This

effect would mostly influence Trps b37. Published energy transfer rates

[49] indicate, that these Trps are the only ones having energy transfer

rates to a heme in the adjacent dimer comparable to the heme in their

own monomer (cf. Table 5. in [49] ). The known strong dependence of

energy transfer efficiency on the donor-acceptor separation explains the

significant quantum yield effect. This argument is further supported by

literature data, available for Trp fluorescence lifetime of HbA [50]. The ra-

tio of a long component of the Trp lifetimes was shown to increase with

pressure, and was attributed to pressure induced changes in the quater-

nary structure. In the case of the multimeric Hb of Lumbricus terrestis, a

similar change in Trp fluorescence was also observed[62]

3.4.1.4 Concentration dependence

The concentration dependence of the transition pressure is shown in Fig-

ure 28, it clearly supports the tetramer dimer transition model : dis-

sociation reactions are known to depend strongly on the concentration


of the initial molecule, while this dependence would not be expected for

unfolding or denaturation reactions. Also, if the observed effect would be

due to a possible shift in the ratio of possible different sub-populations in

the T state1, a concentration dependence would not be expected. Besides

the pressure-induced red shift and intensity increase in Trp fluorescence,

also a significant broadening in the Trp emission band can be observed.

This can be attributed to an increased heterogeneity in the fluorescent

Trps when dimerization takes place. The broad initial (atmospheric) Trp

emission spectrum reflects also to an initial heterogeneity of the fluo-

rescent Trps, which can be partially also attributed to the existence of

conformational sub-populations.

3.4.1.5 Pressure induced dissociation is well known

High pressure dissociates protein oligomers by squeezing water molecules

into the voids. This model was experimentally verified by H/D exchange

experiments[135]. Theoretically this is also expected since ordered watermolecules have a smaller volume than those in the bulk solution, and thus based

on the LeChatelier-Braun principle, the disintegration is favorable un-

der increasing pressure. High pressure induced dimerization - and also

monomerization - of HbA have been previously demonstrated based on

fluorescence labeling and anisotropy measurements [105]2.

Based on these considerations, it is very likely that the observed changes

in Trp fluorescence under high pressure report on the change of the

tetramer dimer equilibrium. In the next section I will present a sim-

ple model, which relates these changes to the observed changes in the

emission spectra.

3.4.2 A simple model of the pressure-induced dissociation

First we define a parameter a for the degree of dimer formation such,

that a = 0 represents the fully tetrameric state, and a = 1 represents the

total dissociation, i.e. the fully dimeric state. Thus the concentration of

1 The T-state population is known to be a sum of multiple conformational sub-populations,this is referred to as the “plasticity” in the T-state. This is more pronounced in hybridhemoglobins than in the native deoxy HbA [111, 112, 113, 87].

2 These data are, however not fully comparable with our results, since differences in theexperimental conditions (different buffers, pH, and sample preparation methods) areknown to influence the stability of the HbA tetramer. We used pH7.4 where HbA is pri-marily in the tetrameric form. Also, there was no attempt in [105] to calculate dissociationconstants from the data.


the tetramer [T] and dimer [D] forms can be expressed with a, and the

total protein concentration C0:

[T] = (1− α)C0 [D] = 2αC0 (13)

The dissociation constant Kd can then be expressed as:

Kd =[D]2

[T]=

4α2C0

1− α(14)

Manipulating Equation (14) to solve for a and discarding the negative

solution yields:

α =

√K2

d + 16KdC0 − Kd

8C0(15)

Where Kd is a function of pressure and dissociation - volume (DV)

according the thermodynamic equilibrium:

Kd = Kd0 e

− p∆VRT (16)

Through Equation (16) a is also a function of pressure, and Kd is equiva-

lent to the dissociation constant measured with conventional methods at

atmospheric pressure (Kd0). Substituting Equation (16) into Equation (15)

yields a sigmoid-like function:

α =

√√√√K2

d0 e2− p∆V

RT + 16C0Kd0 e

− p∆VRT − Kd0 e

− p∆VRT

8C0(17)

Taking into account that the spectrum in the first-order approximation

is a linear function of a, e.g., the maximum position of the Trp emission

peak may be approximated with:

λmax = λ0 + α · ∆λ (18)


Table 7: Kd0 and ΔV data of oxy-HbA and Zn-HbA under various conditions,and at 60μM concentration. The relative error of the data is approxi-mately 5%.

Hb typeeffector Kd0 DV

and concentration [;10-6 M] [mL/mol]

oxy-HbA

none (stripped) 1.41 -99.5

100 mM Cl-1.22 -83.2

2 mM IHP 0.47 -97.7

Zn-HbA

none (stripped) 0.44 -105.3

100 mM Cl-0.78 -106.6

2 mM DPG 2.06 -103.6

2 mM IHP 12.9 -83.4

where l0 is the emission maximum position on the wavelength scale at

atmospheric pressure, and Dl is the total spectral shift. This approxima-

tion can be combined with Equation (17) to yield:

λmax = λ0 +

√√√√K2

d0 e2− p∆V

RT + 16C0Kd0 e

− p∆VRT − Kd0 e

− p∆VRT

8C0·∆λ (19)

This function can then directly be fitted to the data shown in Figure 27, In fact the solid linesin Figure 27 arecurves obtained byfitting Equation (19)to the data

to yield the parameters Kd0 and DV. The data obtained with this model

are shown in Table 7.3 The p½ values can be related to this model, they

are the pressure values corresponding to a = ½.

The data show that allosteric effectors distinctly influence the dissociation

constant (Kd0), and the dissociation-volume (DV) in oxy-HbA and Zn-

HbA.

3 The data of BZF are missing from the table. This is due to the fact, that BZF has its ownfluorescence emission, and it interferes with the Trp signal. The half-dissociation pressurep½ can be reliably obtained, but the fitting of Equation (19) can not be performed. This,and further remarks on BZF fluorescence data is discussed in detail in [117]. It has tobe also noted, that the fitting of Equation (19) is an ill-conditioned problem, and thusthe uncertainty of the values (estimated by the s.d. of the fitting to be approximately 5%)may be somewhat larger than the s.d. values coming from the fitting process. Thereforethe use of p½ is also worthwhile.


3.4.3 Analysis of the data

The dissociation model can be further verified, if we express the concentration-

dependence of the p½ values, by solving Equation (17) for a, and then

substituting a = ½ yields a logarithmic function, which is the same as

shown in Figure 28.

pα=1/2 =RT∆V· log

K0

2C0

(20)

A HbA solution is always a dynamic mixture of tetramers and dimers,

however the dimer concentration is usually very low. The dimer-tetramer

equilibrium was extensively studied along with the kinetics of the dis-

sociation [4, 6, 152, 12, 23, 59]. Under our conditions the dimer ratio is

estimated to be less than 1% in the R state of oxy-HbA , and less than 0.1%

in the T state (Zn-HbA). Physiological conditions (high protein concen-

tration, close to neutral pH) shift the equilibrium towards the tetrameric

form. Considering the data for the R state, the determined dissociationThere are manypoints, which can be

discussed to relatethe results to other

data in the literature.This can be read in

[117], I will presentonly the main points

here.

constants (Kd0) agree well with previous reports on R state HbA[6], where

tetramer to dimer dissociation constants were measured in the case of

stripped human oxy-HbA, and also in the case of the IHP-complexed

HbA, the values agree within experimental error. This again very strongly

supports the presented simple model, and the interpretation behind it.

many other dissociation constants were not measured in the literature be-

fore, primarily due to experimental limitations (e.g., the dilution method

would also dilute the effector, while other methods may influence the

oxygen binding, and thus artificially shift the equilibrium).

It is important to note, that in both cases the Kd0and DV data strongly

depend on the presence of allosteric effectors. This further supports the

global allostery model. In the original argumentation for that model was

based on the strong modulation of oxygen-binding (association constants

KR and KT) in both R- and T- states of HbA by these effectors. It is inter-

esting to see, if the changes in the Kd0 values can account for the observed

modulation of the association constants. This we can do for the R state

based on characteristic half oxygen-saturation (P50) values from the lit-

erature [6], P50= 0.4 mmHg for the dimer form and 1.78 mmHg for the

tetramer. As an approximation, we can assume that the proportion of the

dimers is low enough (less than 1%), such that the measured P50 values

can be considered in a first approximation as a linear combination of the

tetramer- and dimer - P50 values. Since from Kd0 we know the propor-


Figure 29: Summary of the changes in equilibria caused by allosteric effectors

R-(αβ)2

T-(αβ)2

oxy-(αβ) deoxy-(αβ)↔

↔↔ ↔

+ ef

fect

ors

+ ef

fect

ors

tion of the dimers, we can estimate the change in P50 caused only by a

change in the tetramer dimer equilibrium. Under our experimental

conditions (i.e. 60µM total HbA concentration, and pH 7.4) and for the

IHP binding to oxy-HbA as an example, we obtain a 10% increase in P50

as an estimate. In the literature, the reported changes in P50 are more thana magnitude higher [155]as an effect of binding IHP, that is, changes in thedissociation constants can not account for the total effect of allosteric effectorson oxygen binding. This again supports the idea, that changes in Kd0

and DVare accompanied by subtle, but important changes in the overall structure anddynamics of the entire tetramer.Finally, the changes in the equilibria caused by allosteric effectors are

summarized in Figure 29.

Double ended arrows represent the equilibria, and dashed arrows show

the influence of allosteric effectors. The changes in these equilibria are mostprobably a direct consequence of tertiary structural changes propagating fromthe effector binding sites to the dimer interfaces in both quaternary states.4

4 There are more possible speculations, but these will be presented in chapter 5. In short,most probably the changes caused by allosteric effectors are being indirectly monitoredby the dissociation parameters, and the primary change may be in the dynamics, whichwill then affect the overall interface tightness, and strength.

4R E L AT I O N T O C O M P R E S S I B I L I T Y

4.1 introduction to fluorescence line narrowing

Fluorescence line narrowing (FLN) is a high resolution technique[100],

which is often used to study the vibronic energy map of a given chro-

mophore. It requires cryogenic temperature, to decrease the vibrational This is a very basicintroduction to theuse of FLN,interested readersare directed toexcellent reviewarticles[37, 91, 134, 36]

coupling to the matrix, and also to increase the Debye - Waller factor

(and also reduce temperature-broadening), and narrow laser excitation

to achieve resolved fluorescence emission spectra. Since at low ( approx-

imately 10K) temperature there are very few thermally induced excita-

tions, and conformational transitions can almost totally be excluded, the

excitation by a narrow - bandwidth laser source excites only certain sub-

populations (in the electronic transition-energy) of the chromophore. This

is emphasized in Figure 30, where in the upper figure panel “A” shows

a number of chromophores being randomly distributed on the energy-

scale. Every molecule has a distinct (0,0) → (1,0) electronic transition

energy, since it is perturbed by the protein matrix, and every protein

molecule of the ensemble has a somewhat different 3D structure, which

is then reflected in a distribution of the transition energies around a mean

value (as the structures are distributed around the “average” structure).

We can order these molecules according to their (0,0) → (1,0) electronic

transition energies, as seen in panel “B”. As a first approximation, it can

be supposed that in every chromophore the (0,0) → (1,0) transition en-

ergy is perturbed by its protein environment, but within a given elec-

tronic band the energies are not changed with respect to each other, thus

all the (1,0)→ (1,i) energies are the same in all chromophores1, thus the

lines in panel “B” are parallel. As a model, the distribution of the (0,0)

→ (1,0) transition energies are assumed to be Gaussian, but it can be any

other distribution as well. The bottom figure shows the situation during a

narrow-band laser excitation. A laser with eg energy and Deg bandwidth

(shown on the right as an arrow, and black horizontal line through the

distribution-map) is resonantly exciting some sub-populations of DNp

1 This means that only the electronic states of the chromophore are perturbed by the sur-rounding protein matrix. If this is not the case, then it only adds another correction-factor,but it does not change the main theory

79

80 4.1 Introduction to Fluorescence Line Narrowing

Figure 30: Demonstration of the FLN technique. Upper figure shows the order-ing of molecules on the energy-scale, bottom figure shows the fluo-rescence emission by a narrow-band excitation. See text for details.Figure reprinted with permission from [68]

rand

om se

ries

orde

red

serie

s


Figure 31: Comparison of room-temperature emission spectrum (blue line) andFLN resolved emission spectrum (red line) of Zn-HbA.

16500 17000 17500wavenumber [1/cm]

fluor

esce

nce

inten

sity

[a.u

.]

, DNq and DNrsizes. Each sub-population has a different absorption

quantum-yield, and also a distinct emission quantum-yield. On the F - e

scales the individual emissions of the sub-populations are shown, while

on the left side I - e graph shows the composite emission spectrum which

can be recorded with the instrument. This recorded emission spectrum

is distinct from the room-temperature conventional fluorescence emis-

sion spectrum. In a conventional fluorescence experiment the excitation is

broad-band relative to the FLN: in FLN the bandwidth is approximately

20 GHz in our experiment, while at about 400 nm excitation wavelength

the 5 nm bandpass is equivalent to approximately 104 GHz. This causes

practically all sub-population to be excited at room temperature, and also

the sub-populations freely inter-convert during the experiment. The vi-

brations of the chromophores are also thermally excited, all these factors

lead to a broad emission peak. A comparison is shown in Figure 31, the

conventional spectrum is the same as in Figure 24, but only the part over-

lapping the FLN experiment is shown, converted, and corrected[66] to

wavenumber scale.

As can be seen, the FLN spectrum is resolved, it contains sharp emis-

sion lines resulting from resonant vibronic excitations, superimposed on

a background of broad bands, which are also present due to emissions

from non-resonant phonon-coupled excitations[37, 43] . The spectra taken

under the fine tuning of the excitation frequency allow for determining

the vibrational levels of the electronically excited state, and the inhomo-

82 4.1 Introduction to Fluorescence Line Narrowing

geneous distribution function (IDF) as follows. It is long known, that by

shifting the excitation laser energy (eg) the observed sharp peaks of the

resolved spectrum also shift with the same energy difference as the exci-

tation laser as seen in Figure 33. This can be explained by looking at the

bottom of Figure 30. Let us assume, that we are exciting on the q-th curve,

thus DNq number of chromophores are excited from the (1,q) vibronic

line, which has an Aq absorption quantum-yield. By shifting eg to a new

value, within the same distribution (thus we do not leave the q-th curve

corresponding to Aq), DNq will change according to the overlap of the

laser line-width and the q-th distribution function. The emission energy

of the peak corresponding to this q-th curve will be always shifted with

respect to the eg laser energy by the (1,q) → (1,0) energy difference 2.

Since the laser is exciting in most cases not only one vibronic line, e.g.,

“q” but mostly several others at the same time (in the figure “p” and “r”

too) multiple sharp peaks can be seen in the spectrum at different po-

sition, and they all shift parallel with the shifting of the laser. Since the

intensity of the peak is proportional to DNq at a given laser energy, it is

important to note, that DNqis not only graphically the overlap of the q-th

distribution with the laser line-width, but also the derivative function of

the Nq(e) distribution function. If we plot the amplitudes of the peaks

in a given series, then the ratio of the peak heights wp(e) is proportional

directly to this derivative function, which is the IDF itself. Thus:

ωq(ε) = Aq · ∆N(ε) ∆N(ε) = k ·∆N∆ε· ∆εg (21)

As can be seen in Equation (21) the IDF (DN/De) differs only by a con-

stant from wp(e), the normalized peak-height function. Since this is true

for every peak-series, to reliably determine the IDF of a given sample, it

is important to simultaneously track every series, and then fit the “peak-

height” distributions together.

While the individual vibronic distributions themselves are also reporting

on the environment of the chromophore3, it is more interesting to re-

late the IDF to the dynamics of the system. According to the fluctuation-

dissipation theorem of statistical physics [76] the volume fluctuations < V

2 which is constant in a first approximation. If not, then it can be seen as a non-linear, nonparallel shift of the emission peak with respect to the laser energy shift.

3 And thus changes in the vibronic energy map would report on changes in the surround-ing protein structure. It can also be estimated that the “range of sensitivity” is a few Å,since the solvent shift of a given chromophore in a given protein is caused by electrostaticand dispersive interactions[13] which both fall off by R-n.


- < V >> of a system - arising from conformational dynamics in a protein

- can be characterized by its compressibility (k):

< V− < V >>=√

κkT < V > (22)

where V is the volume of the protein, k is the Boltzmann - constant and

brackets denote averaging. Since the volume fluctuation is proportional

to the square - root of the compressibility, determining the compress-

ibility at higher pressures than physiological can also reveal important

aspects of protein dynamics. The volume fluctuations will still be not too

large to destroy the structure, if denaturation due to pressure can be cir-

cumvented. A cryogenic method is well suited to this task, since in the

frozen state denaturation is not expected to occur,even at very high pres-

sures, because the boundary of the protein is firmly bound to a solid ma-

trix. This inhibits any large-scale conformational change, thus prevents

the denaturation of the protein.

As can be seen from the room-temperature data in Figure 24 the broad

emission shifts with pressure. A similar shift by pressurization of the IDF

determined by FLN can also be observed. The compressibility can be cal-

culated from this shift of the IDF, as described in detail in [126]. In short,

the shift of a given spectral line from n0 to np under pressure is propor-

tional to the solvent shift (n0- nvac ) of the environment, where nvac is the

vacuum frequency, the wavenumber, where the given chromophore in a

hypothetical situation - of being in the absence of environmental interac-

tions, but with unchanged conformation - would absorb light. In a linear

approximation and supposing that the effect of the environment can be

described with a potential proportional to R-6 distance dependence, the

model leads to the formula[74]:

νp − ν0 = 2(ν0 − νvac)κp (23)

This model was used successfully to describe pressure induced shift

of the optical transitions in glassy matrices, and also in proteins [43, 158,

157]. In the case of the shift of the IDF, one has to consider not a single

spectral line - as being the case in Equation (23), but a distribution of

the solvent shift values. If we assume a normal distribution, or a sum of

normal distributions, then it can be calculated that:

ν0p = ν00 + 2κp · (ν00 − νvac) σp = (1 + 2κp)σ (24)

84 4.2 Compressibility results

where the extra “0”-s in the indices emphasizes the fact that this cor-

responds to the center of the normal distribution, and sv is the width of

the normal distribution. If the IDF can be approximated by a normal dis-

tribution, then Equation (24) also holds for the IDF4. It can be seen, that

the shift of the IDF is also accompanied by a broadening if the pressure

is increased. The slope of both the broadening and the shift on the en-

ergy scale is proportional to the compressibility, and thus to the volume

fluctuation of the system. In the next section data obtained from Zn-HbA

under different conditions is presented, and discussed.

4.2 compressibility results

The experimental setup was the following:

For the FLN experiment we used a Coherent 899-01 ring dye laser pumped

by an Coherent Innova 307 Ar-ion laser. The dye used for excitation was

Rhodamine 560 or 590 (Exciton Laser Dyes). The spectral width of the

laser line was 0.5 cm-1,the output power was 0.3 ... 0.6 mW/mm2. Flu-

orescence emission was collected at approximately 35° angle relative to

excitation and focused into a THR 1000 monochromator (Jobin-Yvon). For

detection a CCD camera (WR CCD-4679 DV401-BV, Andor Technology)

cooled to -65°C was used, mounted at the exit slit of the monochro-

mator. Integration time was 20 ... 60 s for each spectrum. The sample

was maintained at 10 K inside a diamond anvil cell with a closed cycle

M22 cryostat (Cryophysics SA) equipped with a Model-330 auto-tuning

temperature controller (Lake Shore Inc). Pressure inside the cryostat was

10-2mbar, it was monitored with a model AGD-101-L Pirani-gauge (Ed-

wards High Vacuum International), and a vacuum was generated with a

rotary vacuum pump (model RV5, Edwards High Vacuum International).

The concentration of Zn-HbA was 60µM in 50% v/v glycerol:buffer so-

lution mixture (buffered to pH7.4 with 100mM HEPES). Pressure was

adjusted with helium gas in the special low-temperature diamond anvil

cell (Diacell Products). This cell of 40 nl volume allows for applying pres-

sures in the range of 0 ... 2 GPa. A ruby chip frozen into the sample

was used for the pressure determination[38], which also made it possible

to check the temperature inside the cell [151]. The accuracy of the pres-

sure values measured at low temperatures was typically 0.2 kbar. The

schematic representation of the experimental setup is shown in Figure 32.

4 If the IDF can be approximated by the sum of normal distributions, then each Gaussiancomponent will have its own shift and broadening.


Figure 32: Schematic representation of the FLN experimental setup. The bottomleft picture shows the photograph of the diamond cell mounted onthe cold-finger of the cryostat, the small mirror is used to direct theexcitation light (green line) to the sample, while the big mirror isplaced into the setup for photographic purposes, only to show theother side of the cell. The upper right picture shows the setup withthe cryostat closed and operating.

Ar i

on la

ser

dye

ring-

lase

rsc

anni

ng

mon

ochr

omat

or

CCD

computer

membrane

Diamond cell in the cryostat

As discussed in the introduction, the IDF can be calculated by follow-

ing a single peak of the resolved emission spectrum, and determining

the amplitudes at each excitation laser energy. The IDF can then be deter-

mined from any of these series, but most reliably from all series together.

As can be seen in Figure 33 already in a few spectra many peaks can

be found, and they all have to tracked individually, and “peak-heights”

have to be determined. It is also important to subtract the non-resonant,

phonon - coupled, excitation - background. I have written a software

package (“IdfFit” 5) to automate this task. The software is custom-designed

to also allow for the wavenumber - calibration of the CCD camera at-

tached to the monochromator in the experimental setup, and it outputs

5 For a more detailed description see Appendix Section §B.2.


Figure 33: A sample series of resolved spectra. The sample is Zn-HbA + 100 mMNaCl at 1.4 kbar. The spectra are shifted along the intensity axis forclarity. The excitation laser scanned the range of 17840 cm-1 ... 18214

cm-1.


Figure 34: The IDF of Zn-HbA + 100mM NaCl at 1.4 kbar. The figure shows theraw output of the IdfFit program as an illustration of the calculationof the IDF. The program also reports the parameters of a Gaussianfitting to the data.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

16500 16600 16700 16800 16900 17000 17100 17200 17300 17400

norm

aliz

ed p

eak a

mplit

ude [a.u

.]

wavenumber [1/cm]

This is IdfFit (c) 2004 G. Schay ; fit parameters a1 m1 s1 a2 m2 s2

[1;17009.2;51.2543;0.161682;16952.2;215.957]std.devs:

[0;1.2;1.6;0.026;26;31]

bZnHb+Cl | p=1.44kbarNormalized data

fitted idf

both the IDF, and a tracking-report of each peak-series. Typically 120 ...

160 spectra were recorded and processed at each pressure level, Figure 33

shows only a fraction of these for clarity. An example IDF calculated from

this spectral series is shown in Figure 34. As can be seen, the main compo-

nent of the IDF is a single normal distribution, thus Equation (24) can be

used to estimate the compressibility6. The IDF also shifts with increasing

pressure, as shown in Figure 35. As apparent from the figure, the center

of the IDF on the energy (wavenumber) scale shifts with pressure, and a

simultaneous broadening can also be seen.

6 The program reports the s.d. in percent, see the error bars in Figure 36 for the absolutevalues.


Figure 35: Shifting of the IDF due to increasing hydrostatic pressure. As an ex-ample the IDF-s of Zn-HbA + 100 mM NaCl is shown, and for clar-ity the individual data-points are omitted, and the IDF-s are shiftedalong the vertical axis. The pressure levels in kbar units, correspond-ing to each curve, are shown in the top of the figure. The shift of theIDF-s is not proportional to the pressure increase.

16800 16850 16900 16950 17000 17050 17100 17150 17200

0 1.44 4.77 6.4 9.11 11.7 16.9

wavenumber [1/cm]

ΔN/Δ

ε [a

.u.]


Figure 36: IDF position and width values (with s.d.) for various Zn-HbA sam-ples under pressure.

0 1 2 3 4 5 6 7 8 916750

16800

16850

16900

16950

17000

17050

2030405060708090100110120BZF

pressure [kbar]

IDF

cent

er [1

/cm

]

IDF

wid

th [1

/cm

]

0 5 10 15 20 2516750

16800

16850

16900

16950

17000

17050

405060708090100110120130140IHP

pressure [kbar]

IDF

cent

er [1

/cm

]

IDF

wid

th [1

/cm

]0 5 10 15 20

16840

16880

16920

16960

17000

17040

405060708090100110120130140chloride

pressure [kbar]ID

F ce

nter

[1/c

m]

IDF

wid

th [1

/cm

]

0 5 10 15 20 2516750

16800

16850

16900

16950

17000

17050

405060708090100110120130140stripped

pressure [kbar]

IDF

cent

er [1

/cm

]

IDF

wid

th [1

/cm

]

The FLN experiment was performed on Zn-HbA in the stripped con-

dition, with 100 mM Cl-, 2 mM IHP and 10mM BZF. The shift of the IDF

center positions on the energy scale, and the width of the IDF at various

pressure levels are shown in Figure 36. It can be seen that the shift of

the IDF fits relatively well to the linear model predicted by Equation (24),

although at pressure values above approximately 15 kbar deviations may

be found (e.g., in the BZF figure, the position of the last point at high

pressure is an outlier, most probably due to some change around the

chromophore), and the elastic compression model may not hold at very

high pressure values. It can also be seen that the slope behaves in a simi-

lar manner, the shift being linear up to about 15 kbar. This indicates, that

90 4.3 Discussion of compressibility

by raising the pressure over this limit, a possibly local structural change

happens around the chromophore.

4.3 discussion of compressibility

The deviation from linearity at very high pressure values may arise from

local non - isotropic changes in the structure around the chromophore.

This may involve a slight rearrangement of side-chains, which can lead

to a change in the interactions between the chromophore and the pro-

tein matrix. This change is reversible, since we have always recorded an

absorption spectrum also after the FLN experiment, and no significant

changes were found in any samples. Although a slight change can not be

excluded, significant rearrangements certainly do not take place.

The lines in Figure 36 indicate a linear regression to the data, the param-

eters of the regression are listed in Table 8. As apparent from the table,

there is a slight change in the slope of the IDF - center-position vs. pres-

sure data upon the addition of allosteric effectors. This change is almost

within the error, and in the case of BZF the direction of the change is

inverse with respect to the change caused by chloride or IHP. It can also

be seen, that the center of the IDF at atmospheric pressure (n0) does not

depend significantly on the presence of allosteric effectors. This may in-

dicate, that the effectors do not cause a significant reorganization of the

protein structure around the chromophore, at least not in the sensitivity-

range of this method (which is a few Å). This is also seen in Figure 37.

The same conclusion can be drawn from the broadening data, the slope

is positive, as expected, but the change caused by allosteric effectors is

almost within the s.d. range. Since the vacuum-frequency (nvac) is not

known for Zn-PP in Zn-HbA, therefore the compressibility values can

not be calculated, but it is not the absolute value of the compressibility, whichis important in the interpretation of the data, but more the change caused by al-losteric effectors. The presence of only a very small effect can be related to

the previous results, but the relation is not straightforward, and also not

ambiguous. Therefore my thoughts about a possible interpretation better

fit in the speculations section of chapter 5


Figure 37: Overlay of the IDF shifts of Zn-HbA in the stripped (red, squares),with 100mM NaCl (green, triangles) and 10mM BZF (orange, trian-gles).

0 5 10 15 20 2516800

16850

16900

16950

17000

17050

pressure [kbar]

IDF

cent

er [1

/cm

]

Table 8: Parameters of linear regression of the shift of the IDF data. Note, thatthe slope of the IDF-center (dν0/dp) is proportional to the isothermalcompressibility (κ).

Zn-HbA slope (dν0/dp)s.d.

dΔν0/dps.d.

ν0 s.d.Δν0 s.d.

sample [cm-1/ kbar] [cm-1/ kbar] [cm-1] [cm-1]

stripped -7.7 ± 0.5 2.3 ± 0.2 17025 ± 5.6 45.4 ± 1.6

100mM Cl- -6.7 ± 0.9 2.6 ± 0.3 17029 ± 7.9 44.7 ± 3.1

2 mM IHP -9.5 ± 1.0 3.6 ± 0.5 17034 ± 10.7 44.9 ± 6.1

10 mM BZF -5.2 ± 0.6 3.4 ± 0.9 17028 ± 2.2 36.9 ± 3.4

10 mM BZF-8.7 ± 1.8 4.3 ± 0.9 17034 ± 7.6 35.3 ± 3.6

with last point

5S U M M A RY

Conclusions from the activation of the global dynamics:

• Thermodynamic parameters (activation - energy and - entropy) of

the dynamical activation can be calculated, these are specific to the

protein (see the difference between Zn-HbA and Mb).

• The protein’s own internal, intrinsic, slow (ms ... s timescale) global

dynamics can only be monitored in a solvent free from anti-freeze

agents.

• The monitored dynamical activation is a global phenomenon of the

entire protein molecule, since it does not depend on the type or

position of the reporting chromophore.

• The activation parameters change significantly if allosteric effectors

are added to Zn-HbA, and the change is in accordance with the

efficiency of the effector in O2 binding (stripped < chloride < IHP

≈ DPG < BZF).

Conclusions from the pressure perturbation study:

• The Trp fluorescence signal shows a sigmoidal transition, which

can be attributed to the tetramer→ dimer dissociation

• By fitting a simple model to the data the atmospheric dissociation

constant, and the volume-change during dissociation can be calcu-

lated.

• These parameters again significantly change in both oxy-HbA and

Zn-HbA upon the addition of allosteric effectors, again approxi-

mately in accordance with the efficiency of the effector.

• The change is in the opposite sense in oxy-HbA and Zn-HbA, in

the latter case the inter - dimeric interface is becoming weakened

by the addition of effectors, which is manifested in the increase of

the dissociation constant.

Conclusions from the compressibility (or accurately, from the IDF-shifting)

data:

93

94

• The shift of the IDF is linear with pressure.

• Slight deviations from the linearity can be found at pressure levels

above 15 kbar, which may indicate a local reorganization of the

protein structure above a certain pressure level.

• The changes in compressibility (thus in the broadening of the IDF

and in the slope of the shifting of the center if the IDF) due to the

addition of allosteric effectors is minuscule, and probably within

the error range. However, the directions of the change are again in

accordance with the efficiency of the effector, with the exception of

BZF.

There are many parallel findings in these conclusions, most notably that

all the calculated parameters seemingly depend on the presence, and

type of allosteric effectors. This shows that there has to be a global change

in the behavior of the protein. The global nature of the change arises most

strongly from the results of the new phosphorescence method. It is of

significance that the activation parameters do not depend on the position of thechromophore inside the protein matrix. The absence of significant changes

in the room temperature absorption and fluorescence spectra, however,

exclude the possibility of significant tertiary structural reorganization, at

least around the Trps and Zn-PPs of the protein. It has to be noted, that

both type of chromophores are in key positions not only for the tetramer

→ dimer dissociation, but also for the R T transition, and thus oxygen

binding.

If we exclude the possibility of significant tertiary structural changes,

than the significant variations in both the inter-dimeric interface binding-

strength, and in the activation parameters of the global slow dynamics

have to be explained in a different way. Let us take a look again at the

activation parameters! The calculated energy and entropy values are consis-tent with a fair sized, transiently opening cavity. This cavity is not static, itopens only for a very short time, and forms a passage for the quencher (oxy-gen) in the structure. This way the oxygen molecules can “hop around” in theprotein matrix, with a step-size of the size of such a cavity. Taking the de-

naturation entropy [69] of approximately 30 cal/(mole K residue), the

observed entropy change is equal to the denaturation entropy of 2 ...

5 residues. The energy change is also in the order of a few H-bonds,

thus the data are consistent with this idea. In Mb possibly similar “traps”

were seen by crystallography experiments under Xe gas, or by transient

Laue-crystallography, in which the hopping of CO in Mb was observed

[136, 25, 130, 16, 15, 19]. In fact, local unfolding was also proposed as a

5 summary 95

mechanism of ligand transfer in Mb [32], which is also consistent with

the theory of transiently opening spaces.

The opening of the cavity is then probably made possible by the on-

going collective dynamics, which may behave analogous to a traveling

compression-wave in a soft material, making some places softer and less

dense, than the others. In the transiently softened parts of the protein a

local cavity can open up making the passage and then rapidly collapse,

thus trapping the small molecule in its new position. This causes a lim-

ited, and of course anisotropic diffusion, the apparent diffusion coeffi-

cient of which will be very sensitive to alterations in the global dynamics

responsible for the softening - hardening of the matrix. In this framework,

the addition of allosteric effectors - as an important (but not sole) effect

- simply modifies these “wave-like” oscillations of the protein structure.

It is also important to note, that these oscillations do not have to alter

the average 3D structure1, thus they would not be detectable by sim-

ple ensemble methods, such as conventional fluorescence spectroscopy.

One can argue, that in the FLN experiment - in which the individual

molecules are each trapped in their own conformation by the solid matrix

- the changes in this global dynamics should be manifested. This is true,

however if the changes in this dynamics are not large, then the conforma-

tional distribution at a given time-point, when the sample is frozen, may

not differ very much from a sample under different conditions (added

effector), and thus the IDFs determined in the FLN experiment may re-

main identical within experimental error. It has to be noted here, that

the individual resolved spectra were somewhat different in each case. It

is also a limitation, that the FLN technique requires a transparent sam-

ple, thus anti-freeze agent has to be added. This may further reduce the

observed effect. A third consideration is also important: in the FLN ex-

periment, at low temperature the Debye-Waller factor is close to 1, while

at the temperature of the dynamical activation it is certainly much lower,

since many vibrations are thermally excited. Thus, while at low tempera-

ture the zero-phonon lines play the major role in the determination of the

IDFs, at the higher temperature of the dynamical activation the phonon-

wings[68] take over the dominance. This change alone may very well

account for the lack of a highly significant change in the shifting of the

1 Since every single molecule has its own global dynamics, and the statistical average maystay within experimental error, if this dynamics is not correlated. And since the moleculesare not synchronized in terms of this dynamical fluctuation, the effects may cancel eachother in the population averaging, if a quasi - static 3D structure is being determined. Ifdynamics is being monitored, then of course the changes will show-up.

96

IDFs2. This consideration raises the apparent controversy between the

very significant changes in the interface-strength data obtained by room-

temperature pressure perturbation, and the lack of any highly significant

effect in the FLN experiment: at room temperature this slow global dy-

namics is already activated, and may play a significant role by influencing

the interfaces as well. If these global oscillations include the interface re-

gion, ie. the amplitude of the oscillations in the interface region is large,

then any changes in these oscillations could - even strongly - influence

the interactions between the two dimer surfaces.

As a summary:

Global, slow dynamics may play an important role in the regulation of

protein function. It may even play a major role in allostery. If we think

about the global dynamics as some sort of collective oscillations of the

structure, than a larger assembly like HbA may have many more types of

these oscillations than a relatively small structure like Mb. Also, if a pro-

tein is small, a significant part of its structure is only a few Å-s away from

the solvent, and solvent-effects may influence its dynamics more strongly.

Thus it may not be “autonomous enough” to build up a sufficiently com-

plex internal dynamics, which would allow for allosteric fine-tuning.

The generalized conclusion of the results on HbA dynamics would be

proved if the elaborated phophorescence method would lead to similar

results in other proteins. Until now the technique was applied for two

other proteins: PGK and dUTP-ase in collaboration with Szabolcs Osváth

and Beáta Vértessy. Results on these two systems are presented - due to

space restrictions only shortly - in the next part of the thesis.

2 This consideration was an important driving-force in the developement of the phospho-rescence method.

Part II

A P P L I C AT I O N T O O T H E R P R O T E I N S

G E N E R A L R E M A R K S T O T H E A P P L I C AT I O N S

In this part two examples of the application of the new optical method

are shown. The two proteins are distinct, phosphoglycerate kinase (PGK)

is a monomeric protein, which has two relatively well separated domains,

while deoxyuridine triphosphatase (dUTPase, DUT) is a homotrimer. They

have a common feature though: the active site for catalysis is not part of

only a single domain or monomer, but in the case of PGK both N- and

C domains of the polypeptide chain play a role in the catalysis moving

towards each other by a hinge - bending motion to form the catalytic site,

and in the case of DUT each of the three catalytic sites is composed of

parts belonging to all three subunits.

In both systems there is much knowledge already about the importance

of dynamics in the function, therefore it is interesting to see if results

obtained with this method correlate with previous knowledge, and are

the results able to also possibly add to- or extend this knowledge. Due

to space restrictions of this PhD thesis, I am not able to go into details in

the literature survey, only the most important facts will be briefly summa-

rized in both cases 3. It also has to be noted, that these are still ongoing

projects. In both cases the data already available enable the drawing of

certain conclusions, but these conclusions probably need to be supported

by additional experiments.

3 This is not a real limitation, since both molecules are chosen only from a pragmaticalpoint of view, to show the possibility of applying the method and theory described in theprevious part of the thesis. Thus, a more detailed literature survey (including the reactionmechanism, proposed models, etc.) would not add to the scope in any significant way,but would overflow the page limit of a PhD thesis.

99

6P H O S P H O G LY C E R AT E K I N A S E

6.1 introduction to pgk

Yeast 3-phosphoglycerate kinase (PGK) is a typical two - domain hinge

- bending enzyme with a conserved primary structure and tertiary fold

including a well - structured inter-domain region[10, 150]. The two do-

mains interact via a helical hinge and through the C terminal helix, which

folds back to the N domain, and proved to be crucial for enzyme activ-

ity [150, 109]. The structure is shown in Figure 38. Contacts between the

two domains are formed through hydrophobic interactions and hydrogen

bonds in the folded structure [146]. There are two tryptophan residues

in the wild-type yeast PGK that can serve as luminescent probes of the

protein conformation [85, 24, 26]. Folding of fragments containing less

than one complete structural domain is incomplete and not cooperative,

but both individual full-length domains (N and C) fold into native-like

structures[99, 63]. PGK therefore is a suitable model to study the mecha-

nism of domain - domain interplay and its role in protein dynamics.

Mutants of histidine tagged PGK, histidine tagged N domain of PGK,

and histidine tagged C domain of PGK were expressed as described

earlier[92, 93]. His-affinity purification was done on Ni-NTA column (Qi-

agen), the purified protein was flash frozen in liquid nitrogen and stored

at -80 °C until use. A model system based on the two-domain structure

of PGK was constructed to study the role of domain interactions on the

dynamics of PGK. The system consists of four mutants (N, C, N*C and

C*N) that contain a single tryptophan residue. The four mutants are log-

ically organized in two pairs. Both pairs contain one individual domain

(either the N or the C terminal domain) and a corresponding mutant

of the intact protein. Within the pair, the single tryptophan residues are

placed at identical positions. This ensures that any changes in the dy-

namical activation between a given pair is not due to the Trp being at

a different position, but rather due to the presence of -, and interaction

with the other domain.

101

102 6.1 Introduction to PGK

Figure 38: Schematic representation of the PGK structure, showing the hinge re-gion as well. The domain abbreviations are shown in dark red color(N, C, N*C and C*N). The sequence differences between the engi-neered constructs is presented in the table below the structures. Fig-ure reprinted from [94] with permission.

Hinge region

N-domain C-domain

N*C

N

C*N

C


6.2 transitions in pgk

The experimental conditions were identical to the phosphorescence quench-

ing experiment of Zn-HbA. I have used the established “fast-cooling”

protocol, the sample contained 20µM of protein in a 20 mM potassium

phosphate (pH 6.2) + 1 mM ethylenediaminetetraacetate buffer. The phos-

phorescence decay curves are shown in Figure 39. Since the signal/noise

ratio was considerably lower as in Zn-HbA, I have tried a third evaluation

which is similar to the MEM, but the distribution is bound to be a sum

of gaussians in the decay-rate space. All evaluations lead to the same <t>within error. This however shows that it is possible to assume a sum of

gaussians in the decay-rate space which may correspond to a distribution

of structures1. Similar to the procedure in the case of Zn-HbA the aver-

age lifetimes2 can be calculated at each temperature. This is shown for all

the four constructs in Figure 40. As can be seen the step corresponding

to the dynamical transition is very different in the four cases. In the case

of the N-domain a relatively sharp transition can be seen, while in the

case of the C-domain a significant broadening with respect to the curve

belonging to the N domain is apparent. This remains to be the case also

in the C*N full length PGK, the broadening blends the end of the tran-

sition into the second transition corresponding to the softening of the

surrounding matrix. A strikingly different curve is seen in the case of the

N*C (ie. the Trp is in the N domain), the dynamical activation seems to

be splitted into two steps. The first step coincides with the step seen in

the N-domain alone, while a second step follows closely which lowers

the average lifetime to the value seen in the case of the N-domain. This

1 This is work-in-progress, the custom-written iterative re-convolution software is currentlybeing developed. Several more decays have to fitted with the software to compare the re-sults with MEM distributions. It can be seen that the overall structure of a given pair ofdistributions are the same, however there are cases in which smaller peaks are missingfrom either of the two distributions. Since in the case of noisy data the classical MEMtends to over-estimate the width of a given peak in the distribution, it is “normal” thatsometimes a single peak in the MEM is resolved into two peaks in the gaussian represen-tation.

2 If we assume that there are distinct sub-populations, based on the MEM analysis, then<t> represents an averaging of the structures. We could try to re-do the analysis pre-sented here for each “sub-structure”, but the assignement of the peaks in the MEM isnot straightforward: as can be seen, everything changes during the transition. It is moreprobable, that the different peaks in the MEM correspond to very similar structures (atleast in the N domain, which is known to fold into a well-defined 3D structure), but withquenchers trapped in distinct locations. These distinct quencher-positions are reflectedin multiple liftime-groups resolved by the MEM.

104 6.2 Transitions in PGK

Figure 39: Sample decays of the PGK N domain construct at various tempera-tures. The line represents the fit to the data as in Figure 2. Two kindsof distributions are shown: obtained by MEM (panels to the right)and by allowing only a sum of gaussian distributions in the decay-rate space (middle panels).

0.01 0.1 1 10 100

0.01 0.1 1 10 100

0.01 0.1 1 10 100

0 5 10 15 20 25 30 35 40 451

10

100

1000

-1

0

1

0 5 10 15 20 25 30 35 40 451

10

100

1000

10000

100000

-1

0

10 5 10 15 20 25 30 35 40 45

1

10

100

1000

10000

100000

-1

0

1

10K

190K

245K

time [s]

time [s]

time [s]

phos

phor

esce

nce

int.

[a.u

.]ph

osph

ores

cenc

e in

t. [a

.u.]

phos

phor

esce

nce

int.

[a.u

.]re

l.err

rel.e

rrre

l.err

rel.

inte

nsity

re

l. in

tens

ity

rel.

inte

nsity

lifetime [s]

lifetime [s]

lifetime [s] 0.01 0.1 1 10 100

0.01 0.1 1 10 100

0.01 0.1 1 10 100

rel.

inte

nsity

re

l. in

tens

ityre

l. in

tens

ity

lifetime [s]

lifetime [s]

lifetime [s]


Figure 40: Average lifetime values of the four different PGK constructs at vari-ous temperatures. The solid lines are the fits to the dynamical transi-tion. The error bars show the s.d. of the data.

100 125 150 175 200 225 250 2750

0.5

1

1.5

2

2.5

N*

temperature [K]

aver

age

lifet

ime

[s]

100 125 150 175 200 225 250 2750

0.5

1

1.5

2

2.5

3

N*C

temperature [K]

aver

age

lifet

ime

[s]

temperature [K]

100 125 150 175 200 225 250 2750

0.5

1

1.5

2

2.5

C*N

temperature [K]

aver

age

lifet

ime

[s]

100 125 150 175 200 225 250 2750

0.5

1

1.5

2

C*

temperature [K]av

erag

e lif

etim

e [s

]

two-step behavior is distinct from the single, broad transition of the C*N

construct. Since the differences between the curves are striking, I have

omitted the derivative curves from the graph in Figure 40 for clarity3.

6.3 inter-domain interactions in the dynamical transition

The results suggest that the two domains of PGK correspond to two dy-

namic units of the native state. Motion of the two dynamic units, how-

ever, is strongly coupled through domain - domain interactions. Inter-

play between the two domains has been shown earlier to be crucial for

3 The derivatives would not aid the conclusions in this case, but instead would just makethe figure more complicated.

106 6.3 Inter-domain interactions in the dynamical transition

Table 9: Parameters of the dynamical activation of PGK constructs.

construct DE DS Kd TMP

type [kJ/mol] [J/mol K] [K]

N 84.1 ± 6.7 445 ± 36 4.7 ± 0.3 189 ± 5.1

C 61.7 ± 5.6 293 ± 26 3.7 ± 0.3 211 ± 9.7

N*C 1 92.1 ± 6.4 494 ± 35 1.5 ± 0.2 186 ± 4.1

N*C 2 (93.4 ± 6.5) (452 ± 31) 2.3 ± 0.2 207 ± 3.9

C*N 74.5 ± 7.2 336 ± 24 1.8 ± 0.2 222 ± 10.8

enzyme function [146]. It can be seen that the interaction between the

two domains has asymmetric effect on the activation of motion in the do-

mains. This seems surprising based on the symmetric structure of the

PGK and the apparently symmetric role of the domains in bringing the

1,3-diphospho glycerate and ADP together for phosphate transfer. The

results of the dynamical activation, however, are in accord with earlier

findings indicating that domain - domain interactions also have an asym-

metric effect on the folding of the domains[94]. The parameters of the

activation are listed in Table 9.

As apparent from the data, there is an asymmetry also in the activation

parameters, the DE and DS values differ significantly in the case of C*N

and N*C constructs, and resemble the difference of the N and C data. In

both pairs (N , N*C) and (C , C*N) the activation energy and entropy

values increase in the full-length construct with respective to the single

domains. This increase is about 10 ... 15%, and somewhat smaller in the

case of the (N,N*C) pair. There is an important and striking difference

between the two curves: in the N*C curve the dynamical transition is

split into two parts, and notably, the activation parameters of the first

step can be evaluated in terms of the presented two-step model. In the

second step, an already somewhat activated dynamics is becoming even

more activated, therefore the the DE and DS values in Table 9 for N*C

2 are in parenthesis, and are over-estimated, since the model assumes an

inactive starting state, as shown in Figure 12. Therefore in this second

case a better parameter is TMP. If we compare the TMP values, then it can

be seen that in the N*C 1 partial activation the systems dynamics is close

to the dynamics of the activated single N-domain, while after the N*C 2

transition it is somewhere between the C and C*N constructs. It has to

be emphasized, that in PGK the two domains are thought to be largely


independent[150], and they supposed to interact mainly through the well-

known hinge-bending motion. This partial autonomy of the domains is

reflected also in the activation parameters. It is important to note, that

according to Figure 12 during the entire activation the outer boundary of

the system is still bound to the solid solvent matrix, thus the well-known,

characteristic hinge-bending motion is blocked. An important conclusionthus follows from the data: even if the hinge-bending motion is blocked, thereis still some communication between the domains in the open configuration ofthe molecule, and this communication is manifested in the coupling of the slow,collective dynamics of the domains. It can be seen best in the case of N*C,

the activation “stops” at a partially activated state as it were somehow

“waiting” for the C-domain to also become active, and then the collective

dynamics finally reaches a fully activated state. This is best seen in the

TMP data, and this coupling is also supported by the increase in the DEvalue, as a larger, but finite sized collective system is expected to have

an increased activation energy. Thus, it could be shown, that the hinge-

bending motion is not the only result of inter-domain communication.

7D U T P - A S E

This is very much work in progress, I have included it though, to show an-

other example of the application of the method. Therefore, and also due

to the space-limit, this chapter is very short, but the preliminary results

obtained so far are interesting, and present a new possible application in

the testing of interfaces of molecules.

7.1 short introduction to dutp-ase

dUTPase (or dUTP-nucleotidohydrolase, DUT) is a homotrimeric molecule,

which catalyzes the dUTP → dUMP + PPi reaction[122]. It is an essen-

tial enzyme responsible for keeping a low cellular dUTP/dTTP ratio and

thus maintaining DNA integrity [44, 140] by keeping their concentration

low, and thus lowering their incorporation into DNA. Although uracil

is tolerated in low incorporation-ratios, if it’s level increases, it leads to

increased probability of double-strand breaks of the DNA, which even-

tually causes cell death. This mechanism explains the importance of the

up-regulation of DUT in tumor cells [22]. The role of DUT in the regula-

tion of tumor cells, and bacteria makes it a target of drug-research, and

the detailed understanding of it’s structure and reaction mechanism is

therefore important [139, 148, 132]. Most DUT enzymes are homotrimers,

with a unique active-site architecture: each of the three active sites in

a trimer is composed of five conserved motifs, four of these motifs are

provided by two adjacent monomers, while the fifth is contributed by

the C-terminal part of the third monomer. This C-terminal motif behaves

much like an “arm”, and is supposed to close-up on the active site dur-

ing the chemical reaction [133, 84, 147]. The structure is shown in Fig-

ure 41. We have used a mutant from of the human DUT, in which a

Trp residue is inserted (F158W) into the C-terminus [147]. It was con-

firmed based on fluorescence changes of the reporting Trp-158 that upon

the binding of substrates the “arm” of the C-terminus is subject to a rear-

rangement, although large conformational changes are unlikely based on

the relatively small changes in the acrylamide - quenching efficiency in

various states (apo - enzyme and bound to various substrates or substrate

- analogs). It was shown, that one of the analogs, 2´-deoxyuridine-5´-(a,b-

109

110 7.1 Short introduction to dUTP-ase

Figure 41: Schematic representation of DUT, the three subunits are colored dif-ferently. The key residues of the active sites are shown in a ball-and-stick model, note the long chain of the “arm” originating from thethird subunits, and reaching the active site. Figure is reprinted from[147].

7 dutp-ase 111

Figure 42: Decay curves of Trp phosphorescence in apo- human DUT at varioustemperatures: 10 K (blue) 210 K (red) and 235 K (green)

0 10 20 30 40 50 60 70 80 90

0

1

2

3

4

5

6

time [s]

log

int [a

.u]

imido)triphosphate (dUPNPP) causes a relatively large change in the flu-

orescence parameters. Therefore this was selected as a staring point. We

have up to now compared the apoenzyme and the dUPNPP-complex, in

order to see if the already observed changes also manifest in the dynam-

ical activation of the system.

7.2 transition in dutp-ase

The phosphorescence decay curves at various temperatures are shown This is a firstanalysis of the data,evidently morestates should beinvestigated to allowfor firm conclusions.These are until thenrather speculations.

in Figure 42. The fitting was done in the same way as described in the

case of Zn-HbA [118] and PGK. The temperature - dependence of the

average lifetime values obtained by the fitting is shown in Figure 43. For

comparison, the lifetime of Pd-CP and stripped Zn-HbA are also shown1. It can be seen, that in the apo-form the lifetime dependence of human

DUT resembles more the case of a free chromophore in a buffer solution

than the behavior of HbA. Although, this behavior is still different from

1 They are scaled-up to 5000ms to fit into the graph.

112 7.2 Transition in dUTP-ase

Figure 43: Temperature dependence of the average lifetime of human DUT inthe apo form (blue squares) and bound to dUPNPP (green trian-gles). For comparison, the fitted curves of Pd-CP (dark green line)and stripped Zn-HbA (red line) scaled up to fit the graph are alsoshown.

120 140 160 180 200 220 240 260 280 300

0

1000

2000

3000

4000

5000

6000

temperature [K]

aver

age

lifetim

e [m

s]

7 dutp-ase 113

the Pd-CP, notably the transition temperature range is significantly lower.

This indicates - in accord with previous findings - that the “arm” region

is not completely exposed to the solvent. Moreover, it can be said, based

on the difference in the activation between the apo-enzyme and Pd-CP

that the “arm” is dynamically coupled to the rest of the protein even

in the open, apo-form. It can also be seen, that the dynamic activation

in the apo-form is a rather broad transition, whereas in the dUPNPP-

bound form it closely resembles the behavior of HbA. This difference

may arise from two factors: First, it can be, that the “arm” is not coupled

strongly enough to the system in the open, apo-form to form a sufficiently

“together-moving” unit with the rest of the protein, thus the activation of

the “arm” may be somewhat separated from the rest of the protein. This,

together with the coupling to the solvent may account for the observed

differences of a higher activation temperature, and significant broaden-

ing of the transition. In short, it can be simply the case, that the “arm”

is somehow in an intermediate state between being fully extended into

the solvent and being tightly bound to the rest of the molecule, and as

a consequence, the activation pattern is a simple “linear combination” of

the closed configuration (dUPNPP-bound) and the Pd-CP curves.

A second possibility is, that in the apo-form there is a considerable struc-

tural heterogeneity in the system, and many different conformers co-exist,

and this is the cause of the broadened transition. If a substrate is bound,

and the “arm” closes, it may trigger a rearrangement in the conforma-

tional space of the molecule such, that the distribution becomes signifi-

cantly narrower, and more resembles a cooperative tetramer such as HbA.

The lower activation temperature, which is in the direction to the activa-

tion of Mb from the HbA-curve, may reflect the fact, that the size of

human DUT is somewhat smaller than tetrameric HbA, but larger than

Mb.

However, since this is not yet a finished study, these conclusions need to

be verified and possibly extended with new experimental data.

8C L O S I N G R E M A R K S

In this section I will briefly summarize the most important conclusions

and add some further thoughts, speculations. It is important to note, that

the speculations are what they are supposed to be: only ideas, which

need further data and experiments to be confirmed, or rejected.

In the first part, which demonstrated the technique in the case of a zinc-

hybrid human hemoglobin (and partly using non-hybrid HbA as well),

the following conclusions were drawn:

• In the temperature dependence of the average phosphorescence life-

time in the 10 K ... 300 K temperature range two separate transitions

can be observed. These transitions do not conform to the previ-

ous observations of a glass-transition as evident from an Arrhenius-

type representation. Furthermore, the comparison of the above tran-

sition with the profile of a free chromophore leads to the conclusion,

that this transition is primarily not an effect arising from the solvent

matrix, but is rather a specific effect of the protein itself.

• The transition can be reliably detected only in the absence of glass-

forming anti-freeze agents.

• The transition can be interpreted in terms of a dynamical activation

of the protein matrix. This dynamics is supposed to be of a slow

(ms ... s timescale) and collective nature. The latter is supported by

the fact that the transition is independent from the position and

type of the chromophore, until the conditions remain the same. Only the mostimportantconclusions aresummarized here,since each chapterand part has its ownsummary

• A qualitative model was built, in which the observed quenching of

the chromophore phosphorescence is caused by an increased dif-

fusion of the small molecule quencher (mainly oxygen) inside the

protein matrix. This increase in the diffusion coefficient is made

possible by an onset of global motions in the structure, which al-

low a “hopping-like” movement of the quencher inside the protein.

Any changes in the activation or type of these global motions are re-

flected in the quenching efficiency and its temperature-dependence.

115

116

• With a simple first-approximation type of thermodynamic model1,

the energy and entropy changes corresponding to the dynamical ac-

tivation can be calculated from the data. These parameters depend

on the conditions of the sample.

• The change in the activation parameters correlate with alterations in

the structure caused by the addition of allosterically active molecules,

and the change follows the trend observable by the biological effect

of these molecules.

• With the help of another simple first-approximation type of model

it was shown that these active molecules influence the strength

of the inter - dimeric interface in both oxygen bound- and deoxy-

states of HbA using pressure perturbation at room temperature and

calculating the dissociation constant of the tetrameric HbA under

different conditions.

• It was also shown by the cryogenic FLN technique, that the com-

pressibility of the protein around the heme-group changes only by

a small fraction, which is just above, or around the experimental

error. However, the order of the change also resembles the order of

the biological effect in this case.

The following ideas can be formulated:

1. It seems probable, that the change in the oxygen-binding function of

1 It has to be noted that in some cases (even in Hb), we have seen an up to 10 ... 20 %decrease in the average lifetime at a range of approximately 5 - 10 K lower tempera-ture than the main transition itself, as can be seen, e.g., in the “N*” data of Figure 40.We have not taken this into account - see the fitted curve in Figure 40 - and it wasalso not always reproducible. It is not considered in this first approximation of the phe-nomenon, therefore we have discarded them from the analysis. It may, however, arisefrom a small-scale, partial onset of the dynamics, which causes a redistribution of thequenchers around the chromophore. It may also indicate that the phase transition couldbe much more complex than be described by this simple model, and it may have an on-set at 5 - 10 K lower temperature. However, these considerations are beyond the scopeof this thesis, and may more data, possibly under different quencher (oxygen) concentra-tions and freezing-speeds would need to be acquired to have enough data to enhance themodel. Importantly, these possible further enhancements would only refine the model,but would not invalidate the present conclusions. It is also important that the dynam-ics, which is being activated in this type of experiment is only some kind of “partial”dynamics, since the boundary of the protein is being coordinated to a solid, still frozenmatrix of the solvent. A possible separate phase-transition in this boundary may furthercomplicate the situation. These considerations however only add to the complexity ofthe problem, but do not significantly alter the conclusions drawn from the very simple,first-approximation type of description presented in this thesis.


HbA is influenced in a dynamical way by allosteric effectors. This means

that the presence of allosteric effectors may modify the slow, global dy-

namics of HbA, and this modified dynamics is what is being reflected in

different ways in the experimental data.

2. Since the FLN technique is cryogenic, thus the vibrations are not 2

excited. This causes the technique to be largely insensitive to the slow,

global dynamics, which is becoming activated only at higher tempera-

tures, generally above 180 - 200 K. The changes in the dynamics may

also have consequences in the low-energy vibrations, and may also mod-

ify the phonon-wing observable by FLN, thus a small effect is expected

which is also seen in the data. Additionally to this change in the phonon-

wings, the distribution of the molecules in the conformational space after

fast freezing may be also changed, if the slow dynamics is changed, since

every molecule will be trapped in its actual conformation at the time of

freezing, and this conformation will not change significantly during the

experiment any more.

3. The importance of dynamics may also explain - or at least is consistent

with - the data obtained by the room-temperature pressure perturbation

study. If there are significant changes in the slow global dynamics of

the tetramer, the inter-dimeric interfaces being part of the system would

also have a fluctuating interaction pattern 3. A changed global dynamics

would certainly cause a re-distribution of the interaction patterns in a

hypothetical dynamical-conformational space, which would then lead to

changes in the average interaction-strength between the two dimers. This

is reflected in the change of the dissociation constant and dissociation

volume.

4. All the above effects are possible without a change in the time or en-

semble average structure, therefore it may be a purely dynamic effect4. This may also help to resolve an apparent controversy, that the al-

losteric effectors bind to the central cavity of the tetramer and affect the

oxygen binding in every monomer at the distant heme-site, but no sig-

nificant, statically observable structural changes happen there. This has

2 or in a very little proportion, as apparent from the high Debye-Waller factor below 10 K3 It can be imagined, that the binding network is not constant in time, but it fluctuates be-

tween several different patterns, and the average is measurable by ensemble techniques,such as Raman spectroscopy or NMR.

4 There is of course a solid experimental evidence coming from a variety of techniques,that the addition of allosteric effectors do change some structural elements, mostly in theinter-dimeric interface region of HbA. However, it is interesting, that at least partly, theobserved changes may result from a dynamical change, and not exclusively from staticchanges of the quaternary or tertiary structure.

118

been incorporated into the models describing the function of HbA by a

changed network of equilibria, and the refined models quantitatively de-

scribe the oxygen-binding curves. However, the structural details are still

not completely understood. The findings presented in this thesis support

the “global-allostery” model published a few years ago. In this model it

is supposed, that tertiary structural changes occur as a consequence of

the binding of allosteric effectors in both oxy- and deoxy- states of HbA.

This can now be extended with the idea, that not only tertiary structural

changes occur, but importantly the pattern of global dynamics is changed,

and this may play a significant, or possibly even major role in the regula-

tion HbA.

In the second part of the thesis, two applications were introduced. The

first is the case of phosphoglycerate kinase (PGK).

• It was shown, that the dynamical activation in both domains will

pairwise a shift to a higher transition temperature, and both activa-

tion parameters increase if the other domain is also present.

• The change of the shift and of the parameters are asymmetric in the

N and C domains.

The change showed up more strikingly in the N domain than in the

C domain, even causing a splitting of the dynamical activation step. In

the C domain the activation corresponds to a broad transition, while in

the N domain a sharp transition is seen. This may reflect the known

fact that the N domain has a very different folding kinetics than the C

domain which is supposed to be a mixture of differently folding sub-

conformations. This is in accord also with the observation, that the dis-

tribution of lifetimes in the C domain at 10 K (data not shown) is much

broader than in the N domain. It has to be noted however, that the dif-

ferent lifetime distribution can also reflect a different local environment,

and is not necessarily a consequence of a global structural heterogeneity

of the C domain.

• Apparently, the hinge-bending motion is not essential for the inter-

domain communication: there is a collective dynamics of the two

domains even when hinge bending is blocked. This finding further

supports the speculation drawn from the HbA data, that the slow,global dynamics plays an important role in the regulation, and most


probably in the function of enzymes 5.

Second, the importance of dynamics is also apparent in the case of dUT-

Pase (DUT). Albeit there are only limited experimental data available up

to now, it can be seen that the apo-enzyme behaves significantly differ-

ently than the substrate-bound form. Both the width and the position

of the dynamical transition are altered if the enzyme is bound to a sub-

strate. The transition is shifted to a lower temperature and the width of

the transition on the temperature scale is significantly reduced. It can be

hypothesized, that the C terminal “arms” fold up to the main structure

and this leads to the modified dynamics. While this folding up is already

known, it is interesting to observe that the dynamical transition of the

apo-enzyme somewhat resembles the transition of a free chromophore

in buffer, whereas the substrate-bound form closely resembles the transi-

tion of a tightly coupled system, namely HbA. This may indicate that in

dUTPase, there is a dynamic coupling between the “arm” and the main

structure, even though the “arm” is also coupled somewhat to the sol-

vent. The ratio of these two couplings change significantly if a substrate

is added to the system. The case of dUTPase also shows that the new

technique presented in this thesis is also capable of monitoring changes

in the boundary region of a large molecule.

For further spculations it is inspiring that in all three - from a structural

and functional point of view - very different cases the importance of slow,

global dynamics is shown and that changes in this specific dynamics cor-

relate with functionally, biologically important events (substrate binding,

inter-domain communication, allosteric control). It may be the case that

these ms - s timescale motions may somehow encode information, which

is transmitted through the structure by a change in this global dynamics.

Different parts of the molecule, albeit being in a relatively large distance,

may “read out” this information simply by being part of those global

fluctuations. Taking into account that most avergage enzyme cycles are

in the time-range around the ms timescale, such a flow of information

may be important in the regulation of these systems. The importance of

5 Of course the importance of dynamics is not new. What is new, is that a specific time-scale (namely the ms - s range), and the global nature of these motions may be especiallyimportant. This is being discovered by NMR as well[86, 143], as recent developementsmake larger and larger systems accessible. An advantage of the phosphorescence-basedmethod is that it can be applied to a protein, or even multi-protein complexes of almostany size.

120

these global fluctuations or dynamics may also be reflected in the fact that

most allosteric systems - or systems which have a lot of fine-tuning possi-

bilities - are fairly large. The larger size may be needed to have “enough

space” to have an internal, independent dynamics, which can then some-

how “store” and “encode” the information needed for the controlling

and fine-tuning of the function.

As a closing remark let us remind ourselves again on the message from

the Bible:

“... for we see now through a mirror obscurely,and then face to face.”

SDG.

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Ö S S Z E F O G L A L Ó

A dolgozatban egy új, foszforeszcencián alapuló módszer kerül bemuta-

tásra, mellyel fehérjék lassú (ma ... s idoskálájú), kollektív mozgásainak

aktivációja vizsgálható. Bemutatom, hogy ez az aktiváció specifikusan a

fehérjére jellemzo. Az aktivációs jelenség kvalitatív és kvantitatív értel-

mezésére is sor kerül egy nagyon egyszeru modell segítségével, amely

azonban a jelenség lényegét leírja, és segítségével meghatározható (be-

csülheto) az aktivációs energia és entrópia. A módszert az elso fejezetben

humán hemoglobin esetében mutatom be, más spektroszkópiai módsze-

rekkel kapható adatokkal együtt. A foszforeszcencián alapuló módszerrel

kapható adatokat összevetem egy nyomás-perturbációs kísérletbol kap-

ható disszociációs állandókkal, illetve a fluoreszcencia vonal-keskenyedés

módszerével kapható izotermikus kompresszibilitás változások adataival.

Megállapítható, hogy hemoglobin esetében mindhárom módszer adatai

korrelálnak az alloszterikus effektorok ismert hatáserosség-sorrendjével.

Mindhárom módszer adatait figyelembe véve feltételezheto, hogy az al-

loszterikus effektorok hatásmechanizmusában a lassú, kollektív dinamika

befolyásolásának fontos szerepe lehet. A második fejezetben bemutatom

az új foszforeszcencián alapuló módszer alkalmazását két másik fehérje,

a foszfoglicerát kináz (PGK) és a dUTP pirofoszfatáz (dUTPáz) esetében.

Foszfoglicerát kináz esetében kimutatható, hogy a fehérje két (N és C) do-

ménje között aszimmetrikus kommunikáció valósul meg abban az eset-

ben is, amikor a szerkezet ismert csuklómozgása gátolt. Az adatok alap-

ján feltételezheto egy más, nem az ismert csuklómozgáson alapuló dina-

mikai kölcsönhatás megléte is. dUTPáz esetében eltérés tapasztalható a

homotrimer molekula C-terminális kar-szeru végének dinamikai viselke-

dése között az apo-enzim és a szubsztrát-analógot kötött forma esetében.

Mivel ez a kar fontos szerepet tölt be az aktív centrum kialakításában,

így felvetodik a kollektív mozgások esetleges szerepe a funkció szabá-

lyozásában, azonban ennek pontosabb tisztázására ebben az esetben to-

vábbi kísérletekre van szükség. Összefoglalva megállapítható, hogy az

új foszforeszcencián alapuló módszer több fehérje esetében is a funkci-

óval összefüggésbe hozható eredményeket szolgáltat, ami felveti annak

lehetoségét, hogy a lassú kollektiv dinamika fontos szerepet játszhat a

több-doménes fehérjék muködésének szabályozásában.

133

A B S T R A C T

A new phosphorescence-based method is presented, by which the acti-

vation of slow (ms - s time-scale) global dynamics of proteins can be

monitored. It is shown, that the activation of this slow, global dynamics

is specific for the protein. A simple model is also presented by which

the activation energy and entropy can be calculated (estimated) from the

experimental data. The new method is presented in the case of human

hemoglobin. The experiments were performed also in the presence of al-

losteric effector molecules, which modify the oxygen-binding of hemoglobin.

As a consequence of the presence of these effectors we have observed

changes in the activation of the collective dynamics of hemoglobin, changes

in the dissociation constant of the tetramer obtained by pressure pertur-

bation, and also changes in the isothermal compressibility obtained by

fluorescence line narrowing spectroscopy. All these changes are in accor-

dance with the efficiency of the effectors in modifying the oxygen bind-

ing of hemoglobin. This shows that changes in the global, slow dynamics

of hemoglobin, caused by allosteric effectors may play a significant role

in the regulation of hemoglobin function. The phosphorescence-based

method is also applied to two other proteins, namely phosphoglycerate

kinase, and dUTP-pyrophosphatase. In the case of phosphoglycerate ki-

nase it was shown that the activation of the dynamics is asymmetric, and

depends on the presence of both domains. Apparently, the hinge-bending

motion is not essential for the inter-domain communication: there is a col-

lective dynamics of the two domains even when hinge bending is blocked.

In the case of dUTP-pyrophosphatase it was shown that the C-terminal

arm-like structures of the trimeric molecule have a distinct dynamics in

the apo-enzyme and in the substrate-bound form. It may thus be hypoth-

esized that the special type of dynamics being monitored in these exper-

iments may be important in the regulation of multi-domain proteins.

134

Part III

A P P E N D I X

G E N E R A L R E M A R K S

It would not be possible to acquire the data presented in this thesis without theuse of custom-designed and custom-built instrumentation. During the years ofmy PhD work, a significant amount if time had to be devoted to engineeringwork. Since this thesis is not an engineering thesis, and there are also spaceconsiderations, I will show only some aspects of the instrumental developments,and will try to give an overview of that side of my work. Would it be an electricalengineering diploma-thesis, then I could explain all the electronics schematics,and all the software codes, but this is not my intention here. This appendix isnot strictly needed to understand the thesis itself, but I think it is important tosee, that experimental science sometimes also involves a lot of engineering. Ihad my joy also in designing and building instruments, and the motivation tohave this appendix is partly to show these results as well.

I

AP H O S P H O R E S C E N C E S E T U P

a.1 system design

The development of a new technique inevitably involves the need of instrumen-tation developments. This case in not different from the others, I first had tochange our old fluorimeter setup, and then gradually build a completely newsystem re-using as many building blocks of the modular Edinburg AnalyticalInstruments (EAI) FL/CD-900 spectrofluorimeter. The need for a new systemarose, when it became clear, that the absence of anti-freeze agents is key to thesuccessful measurement of the thermodynamic activation. This absence of glass-forming substances from the protein solution caused the samples to freeze intoan opaque structure, also having a considerable light-scattering. This resultedin a dramatic decrease of the light intensity at the detector side, since boththe excitation efficiency, and the detectable fluorescence intensity decreased bymore than a magnitude. Even with a cooled, high quantum-yield photomulti-plier (PMT) (Hamamatsu R928, cooled to -65 °C) the photon count / minute onaverage was 50 ... 100 only. To have a reliable fit taking into account the Poissondistribution of the photons (thus the variance is equal to the expectation value)the estimated data acquisition time is in the range of 9 ... 15 hours on average. Ifthe quenching efficiency at the dynamical transition is large, then the signal levelwill decrease significantly, and the needed data acquisition time will increase ac-cordingly. Generally this means, that a single temperature-scan required aroundtwo - three weeks of continuous operation and data acquisition. At each temper-ature one has to wait for equilibrium to be reached, at least in a sense, thatno further significant changes should occur during the data-acquisition time 1.Then, after waiting for equilibrium, the data-acquisition can be started. Afterthat, the new temperature has to be set, and the cycle can restart. While this canalso be done manually, it is practically impossible to have two temperature-scanswhich are exactly the same in terms of all parameters, and this may introducean excess of uncertainty into the data. It is also useful if the data acquisitionis adjusted always to the actual signal level, and not set “by the eye”. A thirdproblem arising from the unusually long time of the experiment, is that shortpower or cooling-water outages can occur. This may not be a problem, if theclosed-cycle helium cryostat is promptly shut down in the event of a drop inthe water-pressure, and it can be re-started as soon the water-flow reaches theminimally required level. To have this done, however a constant, non-stop su-

1 Of course very slowly happening changes can not be totally excluded. If there is a kineticbarrier, thus the system is not perfectly in equilibrium, then the repeatability will evenmore depend on the waiting and acquisition times to be uniform.

III

IV Appendix

Figure 44: Picture of the integrated phosphorescence lifetime spectrometer. Themain blocks are marked in the picture.

cryostat compressor cryostat cold headvacuum-pump

controller electronics

spectrometercontrollercomputer

cryostat control and safety system

pervision, and more importantly rapid intervention to avoid cryostat damage isrequired.All these considerations lead to the design, and build of a computer-controlled,integrated measurement system. The image of the system (in the days when theZn-HbA data were taken) is shown in Figure 44. As can be seen in the first daysthe integration involved multiple computers, they were working in a network,each had it’s own task, and I always had issues with one computer falling out.The next step was to re-design and re-build the whole system to achieve reli-able operation. The block-diagram of the new system is shown in Figure 45. Itis built around the optical building blocks of the old EAI instrument, since itis a modular system, and the building-blocks could be re-used in the new sys-tem. In the new design three main controllers are used: The central controlleris a Linux-based Pentium-I PC (data acquisition and programming unit). Thisruns the main data-acquisition software, which controls the rest of the system,and outputs its data to a web-server (User interface) for display and down-load. This design alleviates the risk of data-loss due to possible over-loadingof the processing capacity of the machine by graphics-intensive tasks. A newer,more powerful PC can not be used, since the these PC-s do not have an ISA-standard card slot. This is however needed for the proprietary controller-cards.The next unit, the Optics controller (OC) is inherited from the original system: it

Appendix V

Figure 45: Block diagram of the new system design.

Optics controller

ExcitationMono

EmissionMono

Sampleholder

PMT

Xeflash

5 ns pulsed solid state laser

Core Control Unit

Multichannelscaler

Data acquisition+

Programming unit

User interface Cryostat

Cooling water+

power control

VI Appendix

is responsible for the monochromators (setting the wavelength to a given value)and the shutters protecting the PMT. For this task the original controller couldbe used, it communicates with a proprietary protocol on an IEEE-488 GeneralPurpose Interface Bus (GPIB-bus). This protocol had to be reverse-engineeredto integrate the original controller into the new design. It turned out to be atext-based communication protocol with added byte-code parts to program thestepping-motor driver cards at system start-up. The third unit (Core ControlUnit, CCU) is a 8-core parallel microprocessor (Parallax Propeller2) responsiblefor the hardware-integration of the solid-state tunable flash-laser, for drivingthe power-electronics of the safety-subsystem, for controlling the cryostat, andfor the timing-synchronization of the light sources (Xenon flash-lamp and thelaser) to the data-acquisition unit. The original multichannel card was replacedby a new photon-counting unit made by Károly Módos based on the photon-counting unit he built for the dynamic light scattering instrument of the depart-ment.

a.2 controller program

The system is integrated via a hierarchical master-slave mechanism: the PC run-ning the main program is the master, and the other two controllers (CCU andOC) are slaved to it. The CCU is however the master of the controller of thesolid-state laser, the Xenon flash-lamp driver, and the power electronics. Thereis an “emergency-network” built into the system, in this system the CCU is theabsolute master. One core of the 8-core microprocessor is dedicated to this net-work, it reads the power and water-flow sensors built into the PMT-cooling lineand into the cryostat cooling line. In the event of an emergency the CCU willpromptly (within a few milliseconds) shut down the cryostat and disable thehigh-voltage on the PMT. It will additionally signal the main program of theemergency situation, so that it can adapt it’s behavior. This prevents damage ofthe system in an event of power or cooling water outage. The main programwill then restore operations if conditions return to normal, an depending on thetemperature of the sample will either terminate the experiment, or return to atemperature slightly below the last setting, insert an extra temperature point (asan internal control of the experiment) and resume the temperature scan. Themain program is also responsible for data-logging. It not only saved the decaycurves, but also periodically logs the temperature, the wavelength, and otherparameters of the system. It created separate files for each decay, but it alsoproduces a single log-file, in which all the data are compressed. This is for con-venience, and also to have a safety-backup of the experimental data. The Linuxoperating system is configured to remotely synchronize the output-directory of

2 http://www.parallax.com/propeller

Appendix VII

the controller program every night to a backup-server. The individual data filesare also synchronized periodically (for eg. in every minute) to the web-server3.

As an example I will show two representative parts of the main controller pro-gram. The code is several thousand lines long, so the whole can not be includedhere.The GPIB initialization, using a custom-modified version of the Linux GPIBcommunication library is shown in 1. The code is well-commented, and doesnot need much additional description.

Listing 1: The GPIB initialization code

1 // *********************************************************************

// EAI comm routine (c) 2008 G.Schay

// uses a hacked linux gpib c API

i n t eaicomm ( char * b u f f e r , i n t * commlen ) /* write it to EAI */

6 i n t c l =0 ;i n t cn=0 ;i n t s t a t u s ;c l = *commlen ;i f (DEBUG)

11 p r i n t f ( " # Sending EAI command : " ) ;f o r ( cn =0 ; cn<= c l ; cn++) p r i n t f ( "%c " , b u f f e r [ cn ] ) ;p r i n t f ( " ; " ) ;

s t a t u s = ibwrt ( dev , buffer , c l ) ;16 i f ( s t a t u s & ERR )

p r i n t f ( " ! ibwrt f ( ) f a i l e d , massage comes :\n" ) ;p r i n t f ( " ! %s\n# " , g p i b _ e r r o r _ s t r i n g ( ThreadIberr ( ) ) ) ;re turn −1;

21 i f ( b u f f e r [0 ]== ’P ’ ) re turn 0 ; /* implement "P" bug of EAI */

/* read back response */

s t a t u s = ibrd ( dev , buffer , 1 0 2 3 ) ;i f ( s t a t u s & ERR )

26 p r i n t f ( " ! ibwrt f ( ) f a i l e d , massage comes :\n" ) ;p r i n t f ( " ! %s\n# " , g p i b _ e r r o r _ s t r i n g ( ThreadIberr ( ) ) ) ;re turn −1;

31 i f (DEBUG) p r i n t f ( " Read from EAI : %s ; bytes t r a n s f e r e d :%d\n" , buffer , i b c n t ) ;

*commlen= i b c n t ;re turn i b e r r ;

i n t e a i i n i t ( char systpye )

36 i n t board_index = 0 ;i n t pad = 1 ;i n t sad = 0 ;i n t send_eoi = 1 ;i n t eos_mode = 0 ;

41 /* PAD=1, board=0, send EOI with last byte of write */

i n t s t a t u s ;i n t commlen ;char b u f f e r [ 1 0 2 4 ] ;

/* EAI monochromator and polariser program sequence */

46 char monoini t fs [ 1 4 ] = 0 x00 , 0 x00 , 0 x00 , 0 x3e , 0 x07 , 0 xd0 , 0 x46 , 0 x50 , 0 x00 , 0 x01 , 0 x4e , 0 x20 , 0 x46 , 0 x50

;char p o l a i n i t f s [ 1 4 ] = 0 x00 , 0 x02 , 0 x00 , 0 x32 , 0 x00 , 0 x01 , 0 x00 , 0 x05 , 0 xf f , 0 xf f , 0 x00 , 0 x00 , 0 x00 , 0 x00

;char monoin i t f l [ 1 4 ] = 0 x00 , 0 x00 , 0 x00 , 0 x3e , 0 x00 , 0 x64 , 0 x03 , 0 x84 , 0 x00 , 0 x14 , 0 x4e , 0 x20 , 0 x46 , 0 x50

;char p o l a i n i t f l [ 1 4 ] = 0 x00 , 0 x02 , 0 x00 , 0 x3e , 0 x00 , 0 x01 , 0 x00 , 0 x05 , 0 xf f , 0 xf f , 0 x00 , 0 x00 , 0 x00 , 0 x00

;char * monoinit = monoin i t f l ;

51 char * p o l a i n i t = p o l a i n i t f l ;/* init board */

dev = ibdev ( board_index , pad , sad , TNONE, send_eoi , eos_mode ) ;

3 nightowl.sote.hu

VIII Appendix

i f ( dev < 0 )

56 p r i n t f ( " ! ibdev ( ) f a i l e d , massage comes :\n" ) ;p r i n t f ( " ! %s\n" , g p i b _ e r r o r _ s t r i n g ( ThreadIberr ( ) ) ) ;re turn −1;

i f (DEBUG) p r i n t f ( " # EAI onl ine : board index=%i , pad=%i , sad=%i \n" , board_index , pad , sad ) ;

61 // System setup sequence.

i f ( systype==FL ) monoinit=monoin i t f l ;p o l a i n i t = p o l a i n i t f l ;i f (DEBUG) p r i n t f ( " # Mode = FL−s t y l e \n" ) ;

66 i f ( systype==FS )

monoinit=monoini t fs ;p o l a i n i t = p o l a i n i t f s ;i f (DEBUG) p r i n t f ( " # Mode = FS−s t y l e \n" ) ;

71 i f (DEBUG) p r i n t f ( " # Runing i n i t sequence\n" ) ;

/* init EAI */

s t rcpy ( buffer , "R, 0 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

76 s t rcpy ( buffer , "R, 0 , 0 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , "M, 2 6 , 0 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

i f ( systype==FS ) 81 s t rcpy ( buffer , " I , 1 , 5 8 0 6 3 " ) ; commlen= s t r l e n ( b u f f e r ) ;

eaicomm ( buffer ,&commlen ) ;i f ( b u f f e r [4 ]== ’− ’ && b u f f e r [5 ]== ’ 2 ’ ) /* mono init error , most probably "Stepper config does not match" Run mono setup */

s t rcpy ( buffer , "P , 1 " ) ; commlen= s t r l e n ( b u f f e r ) ;86 eaicomm ( buffer ,&commlen ) ;

bcopy ( monoinit , buffer , 1 4 ) ; commlen=14 ;eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 1 , 5 8 0 6 3 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

91 i f ( systype==FL )

s t rcpy ( buffer , " I , 1 , 3 9 0 8 2 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

96 i f ( b u f f e r [4 ]== ’− ’ && b u f f e r [5 ]== ’ 2 ’ ) /* mono init error , most probably "Stepper config does not match" Run mono setup */

s t rcpy ( buffer , "P , 1 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;bcopy ( monoinit , buffer , 1 4 ) ; commlen=14 ;

101 eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 1 , 3 9 0 8 2 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

106 s t rcpy ( buffer , "M, 5 , 0 " ) ; commlen= s t r l e n ( b u f f e r ) ; // defaulting to us lamp

eaicomm ( buffer ,&commlen ) ;i f ( systype==FS )

s t rcpy ( buffer , " I , 2 , 5 8 0 6 3 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

111 i f ( b u f f e r [4 ]== ’− ’ && b u f f e r [5 ]== ’ 2 ’ ) /* mono init error , most probably "Stepper config does not match" Run mono setup */

s t rcpy ( buffer , "P , 2 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;bcopy ( monoinit , buffer , 1 4 ) ; commlen=14 ;

116 eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 2 , 5 8 0 6 3 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

121 i f ( systype==FL )

s t rcpy ( buffer , " I , 2 , 3 9 0 8 2 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;i f ( b u f f e r [4 ]== ’− ’ && b u f f e r [5 ]== ’ 2 ’ ) /* mono init error , most probably "Stepper config does not match" Run mono setup */

126 s t rcpy ( buffer , "P , 2 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;bcopy ( monoinit , buffer , 1 4 ) ; commlen=14 ;eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 2 , 3 9 0 8 2 " ) ; commlen= s t r l e n ( b u f f e r ) ;

Appendix IX

131 eaicomm ( buffer ,&commlen ) ;

s t rcpy ( buffer , "M, 6 , 1 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

136 i f ( systype==FS ) s t rcpy ( buffer , " I , 9 , 5 7 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;i f ( b u f f e r [4 ]== ’− ’ && b u f f e r [5 ]== ’ 2 ’ ) /* polariser init error , most probably "Stepper config does not match" Run mono setup */

141 s t rcpy ( buffer , "P , 9 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;bcopy ( p o l a i n i t , buffer , 1 4 ) ; commlen=14 ;eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 9 , 5 7 " ) ; commlen= s t r l e n ( b u f f e r ) ;

146 eaicomm ( buffer ,&commlen ) ;

i f ( systype==FL )

s t rcpy ( buffer , " I , 9 , 6 9 " ) ; commlen= s t r l e n ( b u f f e r ) ;151 eaicomm ( buffer ,&commlen ) ;

i f ( b u f f e r [4 ]== ’− ’ && b u f f e r [5 ]== ’ 2 ’ ) /* polariser init error , most probably "Stepper config does not match" Run mono setup */

s t rcpy ( buffer , "P , 9 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

156 bcopy ( p o l a i n i t , buffer , 1 4 ) ; commlen=14 ;eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 9 , 6 9 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

161 i f ( systype==FS )

s t rcpy ( buffer , " I , 1 0 , 5 7 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;i f ( b u f f e r [5 ]== ’− ’ && b u f f e r [6 ]== ’ 2 ’ )

166 /* polariser init error , most probably "Stepper config does not match" Run mono setup */

s t rcpy ( buffer , "P , 1 0 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;bcopy ( p o l a i n i t , buffer , 1 4 ) ; commlen=14 ;eaicomm ( buffer ,&commlen ) ;

171 s t rcpy ( buffer , " I , 1 0 , 5 7 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

i f ( systype==FL )

176 s t rcpy ( buffer , " I , 1 0 , 6 9 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;i f ( b u f f e r [5 ]== ’− ’ && b u f f e r [6 ]== ’ 2 ’ ) /* polariser init error , most probably "Stepper config does not match" Run mono setup */

s t rcpy ( buffer , "P , 1 0 " ) ; commlen= s t r l e n ( b u f f e r ) ;181 eaicomm ( buffer ,&commlen ) ;

bcopy ( p o l a i n i t , buffer , 1 4 ) ; commlen=14 ;eaicomm ( buffer ,&commlen ) ;s t rcpy ( buffer , " I , 1 0 , 6 9 " ) ; commlen= s t r l e n ( b u f f e r ) ;eaicomm ( buffer ,&commlen ) ;

186

i f (DEBUG) p r i n t f ( " # EAI i n i t sequence f i n i s h e d .\n# System type i s now s e t to %s \n" , (systype==FS ) ? ( " FS " ) : ( " FL" ) ) ;

/* init ready */

re turn 0 ;191

As can be seen, the communication routine is from line 17 to line 47. Thecontroller needs to send byte-code along the text-formed communication to theOC unit at start-up, this is declared in lines 60 ... 65. From line 49 the maininitialization routine follows. This is full of optional debugging messages, theDEBUG variable is set by the main routine.

The photon counting unit also needs special communication, the routine islisted as the code snippet shown in 2.

X Appendix

Listing 2: Communication code of the photon counting unit

i n t acqcomm ( char * acqbuf fer , long commwait ) long counter =0 ;long c n t r =0 ;

4 i n t code =0 ;i n t tempcode =0 ;char s tay =1 ;char tmp=0 ;i n t s lwt =0 ;

9 i f (DEBUG>1) p r i n t f ( " # AcqBoard : command i s : %s\n" , acqbuf fer ) ;i f ( acqbuf fer [0 ]== ’ q ’ ) s tay =0 ;c n t r =0 ;f f l u s h ( acqport ) ;i f ( s tay )

14 i f ( acqbuf fer [0 ]== ’ . ’ ) bzero ( acqbuffer ,BLEN) ;// read resp.

// DataAck resp format: M.....<CR> for every line

counter =0 ;19 code =0 ; tempcode =0 ;

i f ( f g e t c ( acqport ) != ’M’ ) p r i n t f ( " ! DataAqBorad : No response .\n" ) ; // first ’M’ indicates

response , read it and check..

while ( code !=EOF&&counter <BLEN)code= f g e t c ( acqport ) ;

24 i f ( code== ’M’&&tempcode==0x0d ) // new line comes , this is the leading ’M’, skip it, make a space instead.

code= ’ ’ ;

tempcode=code ;29 i f ( code==0x0d ) code= ’\n ’ ; // replace <CR> with \n

i f ( code !=EOF) acqbuf fer [ counter ]= code ;counter ++;

counter−=3;34 acqbuf fer [ counter ] = 0 ;

i f (DEBUG) p r i n t f ( " # AcqBoard : Read response : %s \n" , acqbuf fer ) ;

e l s e f o r ( c n t r =0 ; acqbuf fer [ c n t r ] >0 ; c n t r ++) ;

39 // cntr --;

i f (DEBUG) p r i n t f ( " # AcqBoard : Command length : %d bytes\n" , c n t r ) ;counter =0 ;while ( counter < c n t r )

tmp=acqbuf fer [ counter ] ;44 code= f p r i n t f ( acqport , "%c " , tmp ) ;

// printf("\ncounter=%d , wrote: ’%c’, code:%d\n",counter ,tmp,code);

f f l u s h ( acqport ) ;f f l u s h ( stdout ) ;// printf("next.\n");

49 counter ++;// tmp=0x0a; // linefeed

tmp=0x0d ; // Carriage Return

code= f p r i n t f ( acqport , "%c " , tmp ) ;54 // printf("\ncounter=%d , wrote: ’%c’, code:%d\n",counter ,tmp,code);

f f l u s h ( acqport ) ;f f l u s h ( stdout ) ;

bzero ( acqbuffer ,BLEN) ;counter =0 ;

59 code =0 ; tempcode =0 ;i f ( commwait )

// possible wait needed before resp can be read do it.

i f ( commwait<=1000000) usleep ( commwait ) ;e l s e

64 slwt =( i n t ) c e i l ( commwait/1000000) ;// printf("sleeping for %d sec",slwt);

s leep ( slwt ) ;

69 i f ( f g e t c ( acqport ) != ’M’ ) p r i n t f ( " ! DataAqBorad : No response .\n" ) ; // first ’M’ indicates

response , read it and check..

while ( code !=EOF&&counter <BLEN)code= f g e t c ( acqport ) ;

Appendix XI

i f ( code== ’M’&&tempcode==0x0d )74 // new line comes , this is the leading ’M’, skip it, make a space instead.

code= ’ ’ ;

tempcode=code ;i f ( code==0x0d ) code= ’\n ’ ; // replace <CR> with \n

79 i f ( code !=EOF) acqbuf fer [ counter ]= code ;counter ++;

counter−=3;acqbuf fer [ counter ] = 0 ;

84 i f (DEBUG) p r i n t f ( " # AcqBoard : Read response : %s \n" , acqbuf fer ) ;

re turn ( counter ) ; // read resp length

It can be seen, that the code checks for specific return values, and if a possible

error is found, then it prints a warning.

a.3 micro-controller hub

The CCU consits of a Parallax Propeller chip, and several external electronics tocouple it’s digital low-voltage (3V) logic to the power-electronics of the system.The Propeller is a versatile platform, the chip has eight parallel running pro-cessors, that share a common memory, and I/O lines. The picture of the CCUboard is shown in Figure 46.

The Propeller runs a special interpreted proprietary language called “spin”,but each processor can also be programmed in assembly.

The spin code is again very long, as an example I only show part a simpledebugging version in 3 used for beta-testing, which is small, and for an exam-ple of the assembly code, the programming of a synchronization timer is alsoshown in 4. Both codes are fairly well commented, so I will not add additionalcomments to them.

Listing 3: Beta-testing laser-synchronization code of the CCU

CON2 _clkmode = x t a l 1 + p l l 1 6 x

_ x i n f r e q = 5 _000_000

Rx = 31

Tx = 30

SerialMode = %0000

7 Seria lBaud = 9600

Bl_Pin = 26

OBJS e r i a l : " Mod_Extended_FDSerial "Timer : " t imer8 "

12 VARlong bl inkDeadlinelong blinkDelaylong PerTlong QSWON

17 long MCSONlong ATTbyte Freqbyte Errorbyte s e r i a l _ o n

22 byte cmd[ 2 0 ]byte DEBUGlong PreHT

. . .

XII Appendix

Figure 46: Image of the CCU main board (top, © G.Schay) and block diagramof the propeller chip (bottom, image used with permission from theParallex website)

Appendix XIII

PUB Main | command , ser_cog27 ’ INIT

Freq :=10

Error :=0

PerT :=0

QSWON :=0

32 MCSON :=0

ATT :=150

DEBUG :=1

PreHT :=50

’ make the PIN an output37 dira [ Bl_Pin ] : = 1

command := −1

s e r i a l _ o n := 0

dira [ Rx ] :=0

dira [ Tx ] :=0

42 ’ MAIN LOOPrepeat

’ wait f o r t a r g e t time to be exceededi f cnt > bl inkDeadline

’ toggle the pin s t a t e . . .47 ! outa [ Bl_Pin ]

bl inkDeadl ine := cnt + blinkDelay’ check i f to s t a r t s e r i a l _ d r i v e ri f ( s e r i a l _ o n ==0 AND ( ina [ Rx]==1 AND ina [ Tx ]==1 ) )

ser_cog := S e r i a l . S t a r t ( Rx , Tx , SerialMode , Ser ia lBaud )52 s e r i a l _ o n := 1

waitcnt ( cnt+ c l k f r e q )i f ( s e r i a l _ o n == 1 AND Error <>0 AND DEBUG<>0) ’ there i s an e r r o r msg to send

S e r i a l . s t r ( @_err0 )S e r i a l . dec ( Error )

57 S e r i a l . s t r ( @_nl )S e r i a l . s t r ( @_error )S e r i a l . r x f l u s hError :=0

i f s e r i a l _ o n == 1

62 command := S e r i a l . rxchecki f command <> −1

i f command == " . " ’ a l l commands s t a r t with " . "S e r i a l . RxStr (@cmd)’ we have new data , update delay and c l e a r b u f f e r

67 i f StrComp (@cmd, S t r i n g ( " period " ) ) ’ s e t period timePerT := S e r i a l . RxDecS e r i a l . s t r ( S t r i n g ( "New period time : " ) )S e r i a l . dec ( PerT )S e r i a l . s t r ( S t r i n g ( " x 0 . 1 s " ) )

72 S e r i a l . s t r ( @_nl )i f ( t imer . setup ( PerT , ATT,QSWON,MCSON, PreHT ) )

Error :=2

i f StrComp (@cmd, S t r i n g ( "qsw" ) ) ’ s e t qswitched modeQSWON := S e r i a l . RxDec

77 i f (QSWON)QSWON:=1

S e r i a l . s t r ( S t r i n g ( "Q−switched mode : " ) )i f (QSWON)

S e r i a l . s t r ( S t r i n g ( " ON" ) )82 i f (QSWON==0)

S e r i a l . s t r ( S t r i n g ( " OFF " ) )S e r i a l . s t r ( @_nl )i f ( t imer . setup ( PerT , ATT,QSWON,MCSON, PreHT ) )

Error :=2

87 i f StrComp (@cmd, S t r i n g ( " mcs " ) ) ’ s e t qswitched modeMCSON := S e r i a l . RxDeci f (MCSON)MCSON:=1

S e r i a l . s t r ( S t r i n g ( "MCS t r i g g e r i n g : " ) )92 i f (MCSON)

S e r i a l . s t r ( S t r i n g ( " ON" ) )i f (MCSON==0)

S e r i a l . s t r ( S t r i n g ( " OFF" ) )S e r i a l . s t r ( @_nl )

97 i f ( t imer . setup ( PerT , ATT,QSWON,MCSON, PreHT ) )Error :=2

i f StrComp (@cmd, S t r i n g ( " s t a r t " ) ) ’ s t a r t t imert imer . setup ( PerT , ATT,QSWON,MCSON, PreHT )i f ( t imer . s t a r t == 0 )

102 Freq :=2 ’ on e r r o r s e t low bl ink r a t e

XIV Appendix

Error :=1 ’ s e t e r r o r msg codeATT := S e r i a l . RxDecS e r i a l . s t r ( S t r i n g ( " Laser dr iver s t a r t e d " ) )S e r i a l . s t r ( @_nl )

i f StrComp (@cmd, S t r i n g ( " stop " ) ) ’ stop timer107 t imer . stop

S e r i a l . s t r ( S t r i n g ( " Laser dr iver stopped " ) )S e r i a l . s t r ( @_nl )

S e r i a l . r x f l u s h Listing 4: Assembly timer code of the CCU

−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−| Timer f o r the Laser C o n t r o l l e r || ( c ) 2010 G. Schay || VER. 1 . 1 Beta |

5 −−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− ’CON’ _clkmode = x t a l 1 + p l l 1 6 x’ _ x i n f r e q = 5 _000_000

VAR10 long timerCog ’ This i s in hub ram

long Datareadylong PeriodTimelong Npulseslong QswON

15 long MCSONlong QswDelaylong PMTDelaylong MCSDelaylong Preheat

20 ’PUB mainPUB s t a r t : success

dira [ 7 ] : = 1

dira [ 6 ] : = 1

dira [ 5 ] : = 1

25 dira [ 4 ] : = 1

outa [ 7 ] : = 0

outa [ 6 ] : = 0

outa [ 5 ] : = 0

outa [ 4 ] : = 0

30 ’ setup to do nothing with s a f e paramsPeriodTime :=0

Npulses :=1

QswON :=0

MCSON :=0

35 QswDelay :=15200

MCSDelay :=80

PMTDelay :=14800

Dataready :=1

Preheat :=50

40 ’ Now to s t a r t the cog ,pinLXe := |<7

pinQsw := |<6

pinPMT := |<5

pinMCS := |<4

45 success := ( timerCog := cognew ( @asm_code , @Dataready ) + 1 )wai tcnt ( c l k f r e q /100+ cnt )PUB stop

i f timerCogcogstop ( timerCog~ − 1 )

50 ’ c l e a r the b i t s of output , and s e t them to inputouta [ 7 ] : = 0

outa [ 6 ] : = 0

outa [ 5 ] : = 0

outa [ 4 ] : = 0

55 dira [ 7 ] : = 0

dira [ 6 ] : = 0

dira [ 5 ] : = 0

dira [ 4 ] : = 0

PUB setup ( PT , ATT,QSW,MCS, PreHT ) : ready60 ’ This s e t s up the timer

’ PT i s the period Time in 0 . 1 s increments’ ATT i s the a t t e n u a t i o n f a c t o r 0=max power , 100 = +100us delayPeriodTime :=PTPreheat := PreHT

Appendix XV

65 QswON:=QSWMCSON:=MCSi f QSWONQswDelay :=15200+(ATT* 8 0 )−960

i f (MCSON)70 MCSDelay := 800

i f n o t (MCSON)MCSDelay :=0

PMTDelay := 420 ’MUST be >400

i f ( PT )75 Npulses :=1 ’ i f no QSW, l e t i t f l a s h slow

i f (QswON AND PT>2) ’ but i f QSW i s ON, shor t period , 1 p r e f l a s hNpulses :=PTi f ( PT>Preheat )Npulses := Preheat

80 Dataready :=1

waitcnt ( c l k f r e q /100+ cnt )ready := Dataready ’ i f cog reads the data i t c l e a r s the f l a gDAT

org85 asm_code or DIRA, pinLXe

or DIRA, pinQswor DIRA, pinMCSor DIRA, pinPMT’ pins s e t

90 mov _ t s t , # 0

or _ t s t , pinLXeor _ t s t , pinQswor _ t s t , pinMCSor _ t s t , pinPMT

95 andn OUTA, _ t s tmov head ,PAR

: read mov ptr ,PARadd ptr , # 4

rdlong _pt , p tr ’ get period time100 add ptr , # 4

rdlong _np , ptr ’ get Npulsesadd ptr , # 4

rdlong _Qon , ptr ’ get QSW=ON?add ptr , # 4

105 rdlong _MCS, ptr ’ get MCS=ON?add ptr , # 4

rdlong _qsw , ptr ’ get Qsw delayadd ptr , # 4

rdlong _pmt , ptr ’ get PMT d e l a t110 add ptr , # 4

rdlong _mcsd , ptr ’ get MCS delaywrlong _zero , head

: in f_ loop mov ptime ,CNT ’ get s t a r t of periodrdlong _ t s t , head

115 t j n z _ t s t , # : read ’ i f new data , read i tt j z _pt , # : in f_ loop ’ i f period time =0 do nothing , readmov _ t s t , _np ’ copy npulses

: pulse mov time ,CNTadd time , _ptbase ’ add 0 . 1 sec delay

120 waitcnt time , # 1 0 ’ wait’ b l ind PMT f o r s e c u r i t yor OUTA, pinPMT

’ mov time ,CNT’ add time , _ t r i g t i m e

125 ’ wai tcnt time , # 1 0

’ andn OUTA, pinPMT’ pmt e . s h u t t e r t r i g g e r e d’ now f l a s h l a s e ror OUTA, pinLXe ’ s e t LXe ON

130 mov time ,CNTadd time , _ t r i g t i m ewaitcnt time , # 1 0 ’ wait 12 usandn OUTA, pinLXe ’ c l e a r LXe , t r i g g e r endandn OUTA, pinPMT ’ re−enable PMT a f t e r pulse

135 sub _ t s t , # 1

t j n z _ t s t , # : pulse ’ i f more pulses repeatt j z _Qon , # : waitperiod ’QSW w i l l not f lash , waitmov time ,CNTadd time , _qsw

140 sub time , _pmtwaitcnt time , # 1 0

XVI Appendix

mov p ,CNTor OUTA, pinPMT ’ bl ind PMT againmov time , p

145 add time , _pmtwaitcnt time , # 1 0

or OUTA, pinQsw ’ t r i g g e r QSWadd time , _ t r i g t i m ewaitcnt time , # 1 0

150 andn OUTA, pinQswandn OUTA, pinPMT ’ re−enable PMT a f t e r pulset j z _MCS, # : waitperiod ’ no MCS s t a r tmov time ,CNTadd time , _mcsd

155 waitcnt time , # 1 0

or OUTA, pinMCSmov time , _uss h l time , # 2

add time ,CNT160 waitcnt time , # 1 0

andn OUTA, pinMCS

: waitperiod mov _ t s t , _npmov _ t i c k s , _pt

165 ’ count f o r Npulses: cntpt add ptime , _ptbase

sub _ t s t , # 1

sub _ t i c k s , # 1

t j n z _ t s t , # : cntpt170 ’ npulses time added

’ i f _ t i c k s =_npulses −> end of periodt j z _ t i c k s , # : in f_ loop’ no , need to wait more , do i t in t i c k s

mov time ,CNT175 : w a i t t i c k s add time , _ptbase

waitcnt time , # 1 0

sub _ t i c k s , # 1

mov time ,CNTt j n z _ t i c k s , # : w a i t t i c k s

180 jmp # : in f_ loop’ I n i t i a l i z e d data_us long 80

_ t r i g t i m e long 960

_ptbase long 8 _000_000

185 pinLXe long 0

pinQsw long 0

pinPMT long 0

pinMCS long 0

_zero long 0

190 ’ U n i n i t i a l i z e d datap r es 1

ptime re s 1

_ t s t re s 1

head r es 1

195 ptr r es 1

time r es 1

_pt r es 1

_np r es 1

_pmt re s 1

200 _qsw r es 1

_Qon r es 1

_MCS re s 1

_mcsd re s 1

nextperiod re s 1

205 _ t i c k s r es 1

FIT a.4 web-server architecture

The web-interface is very minimalistic. It is optimized for viewing also on low-resolution devices, such as smart-phones. The reason behind this is, that in

Appendix XVII

an event of emergency the main program also sends an email, and one canpromptly check the status of the system by opening the web-page it generates.The main controller program outputs data files in two formats, one as a text-fileto download, which is simply copied to the server, and a link is inserted intothe HTML-code accordingly. The second file is for processing with the “Gnu-plot” program4 which makes a small image of the data accordingly to the datatype: excitation or emission spectrum, or phosphorescence decay. In the lattercase the decay is shown in a half-logarithmic representation. The content of theweb-site is generated by some very simple commands driving Gnuplot, and theline-oriented file-processor “awk”5. This is possible since the main controllerprogram outputs the files in formats suitable for these programs, and it alsogenerates a text-file from which for eg. the status-message on the web-page caneasily be generated. As an example an image of the website’s page in an emer-gency situation is shown in Figure 47. Note the status message at the beginning,the power status is “OFF”.

4 http://www.gnuplot.info5 http://www.gnu.org/software/gawk

XVIII Appendix

Figure 47: The first page of the web-site of the data-acquisition program as dis-played on a remote computer.

BF L N S E T U P

In the FLN setup, there were two separate tasks to be solved. The first was the

development of a program to help tune the ring dye-laser once it was operating

in a power-stabilization loop-back. The second task was to develop a program

package to help analyze the data.

b.1 laser scanning

The computer control of the scanning was important, since at the edge of thescanning range the laser-dye bleaches more quickly, and to be able to measurethe IDF, the scanning has to be made as quick as possible. With a manual scan-ning this would not be possible. Therefore I have written a very simple Delphilanguage program to run under Windows to control the stepper motor drivingthe scanning mechanics. The choice of Delphi comes from the fact that the CCDcamera’s software also runs under Windows, so this way the whole setup couldbe controlled with a single computer. The image of the controller program isshown in Figure 48. The program is very simple: it first calibrates itself to thespeed of the computer it is running on, and then uses this calibration to outputpulses to drive the stepper motor. Since there is no feed-back of the actual posi-tion, the laser’s wavenumber-position has to be read manually at the beginningof the experiment, and input into the program. Then by pressing the buttons onthe screen the laser can be moved with a given wavenumber-increase or decreaseto the new position. For convenience two different steps are also implemented,

Figure 48: Image of the laser-scanning program, together with a list of files ofthe source code.

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XX Appendix

along with a numeric input possibility.

b.2 data evaluation

The data evaluation on the FLN experiment involves the processing of hun-dreds of spectra. As shown in Figure 35 several peaks in each spectrum can beevaluated, and ideally all of the observable peaks have to be followed, and theposition and the amplitude of the peaks have to be recorded. Another problemis the subtraction of the non-resolved baseline, since that would introduce arti-facts into the peak-height data. Therefore the spectra had to be subjected to abaseline-subtraction first.I have developed a software package written in “octave”1, a free alternative tothe well-known Matlab® program. The package consist of several small pro-grams, each performing a different task. The tasks are the following:

• Calibrating the CCD camera data (turning the pixel-number into wavenum-ber scale). The CCD camera’s image is turned into a quasi-spectrum bythe data-acquisition software, which integrates the image along the ver-tical axis. This is useful, since the camera is mounted onto the exit slitof the monochromator, and thus a given spectral line is a vertical linein the image of the camera. The calibration is done by processing thisvertically integrated image taken of a glimm-lamp through the monochro-mator, and recorded with the camera. The known emission lines of theneon gas can be used to find them in the image of the camera, and makea pixel to wavenumber conversion. I have used a simple linear fit to thepixel-number vs. glimm-lamp emission line wavelength data pairs to ob-tain the calibration.

• Converting the spectral images to real spectra by using the establishedcalibration.

• Baseline-correcting the spectra by removing non-resolved background fromthe spectra.

• Finding and tracking the peaks in a series of spectra, together with thecorresponding excitation wavenumbers.

• Fitting the IDF to the multiple peak-series by a global-fitting algorithm.

The programs were designed in a way to build upon each other, each is process-ing the files from the program before it in the processing chain, and outputs aformat required by the program performing the next step. This makes it pos-sible, that the processing can be halted at any stage, and it opens the way formanual intervention if possible, by simply editing the intermediate files beforerunning the next program on them. For convenience, a wrapper program is also

1 http://www.gnu.org/software/octave

Appendix XXI

Figure 49: Output of the “Peakfinder” program of the FLN data evaluation pack-age. The sample is Zn-HbA + 100 mM NaCl at 1.4 kbar pressure.

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This is Peakfinder (c) 2004 G.Schay ; Following peak: [17024.3,14,678] format:[peakpos,spectrumN

o,pixelpos]

included in the package, which finds all experimental files in a directory struc-ture, and runs the evaluation on each spectral series. It also prints a report ispostscript format about every stage. As an example of the outputs generated bythe package such a report from the peak-tracking stage (“Peakfinder” program)is shown in Figure 49.

A phosphorescence method to probe protein dynamics

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